Kenneth A. Getz

The acceleration of drug discovery and development has taken on even greater importance as we face a third year of the COVID-19 pandemic. The industry has responded by incorporating remote monitoring techniques and fast-tracking the use of hybrid and decentralized clinical trial (DCT) models, at a pace never seen before. To sustain the momentum on these and other innovations that support study execution, we have also seen the rise of the #NoGoingBack initiative which aims to ensure that the progress made doesn’t fade when the pandemic finally fades.*

Despite these short term achievements, it is still taking more than 20 years to reach industry-wide adoption of various technologies and innovations that could prove beneficial to clinical research operations. Interactive Voice Response Systems (IVRS) and Electronic Data Capture (EDC) solutions were introduced in the late 1980s and early 1990s but these are only now reaching wide adoption

 by sponsors and CROs. Electronic Patient Reported Outcomes (ePRO), Electronic Clinical Outcomes Assessment (eCOA), and eSource technologies, while introduced in the mid to late 1990s, have yet to achieve wide adoption.

 This pattern holds true for risk-based monitoring, digital health outcomes, and other innovative approaches and solutions. While these innovations offer great promise, their potential can’t be realized if it takes two decades or more for them to be fully embedded into the drug development process.

In a first attempt to understand the factors impacting technology adoption, a 2020 Tufts CSDD study revealed that financial and regulatory concerns topped the list.

 Lack of trust in the technology was also reported as an important factor in that study. Additionally, it also revealed that organizational culture and senior leadership’s approach presented significant challenges to the process of technology adoption.

To gain further insights into the barriers to and opportunities for accelerating innovation adoption at both the industry and company levels, the Tufts Center for the Study of Drug Development (Tufts CSDD) undertook additional research in 2021. The purpose of this research is to characterize the long term adoption experience of technologies and capabilities supporting clinical trial execution. This research takes a long term view, and since we have yet to see the permanence of the changes that are taking place during the Covid-19 pandemic, these changes were not the focus of this research.

The research comprised informational interviews and an online global survey of biopharmaceutical executives and clinical research operations personnel. The research was completed in collaboration with WCG Avoca and seventeen biopharmaceutical sponsors who formed the working group (WG) participating in the project.

This article will provide some high-level findings from the research with a focus on actionable steps that biopharmaceutical executives can take to foster and support the adoption of innovations within their companies, namely:

Instituting mandates for greater operational efficiency

Greater support, involvement and engagement by senior leadership throughout all stages of the innovation adoption process

Offering incentives and recognition—and eliminating penalties—to individuals who promote innovative behaviors, approaches, and technologies within the organization; and

Implementing better change management, planning, and communication activities early on, and throughout the process.

The Primary stages of innovation adoption

Two predominant models exist that provide context for how innovations are adopted. The first model is the Gartner Hype Cycle, developed by Fenn in 1995. The second model is known as the Innovation Diffusion Model, developed by Rogers in 1963.

The initiation stage involves identification of the need to try a different technology, process, system, or approach to optimize clinical trial execution. This is where organizations gauge the interest and start the initial planning for trying or testing out an innovation. This is followed by the evaluation phase, which typically involves pilot projects or other assessments of the potential innovation. Based on results from the evaluation phase, organizations typically go through a decision-making process to either abandon or move forward with enterprise-wide adoption of the innovation. This is finally followed by a series of communications and training activities in support of broad implementation of the innovation throughout the organization.

These models informed the development of an interview guide and global survey. Twenty interviews were conducted with various stakeholders from the working group’s member companies. The interviews provided insights into the stages and decision-making processes that sponsor organizations follow to identify and evaluate potential innovations in the clinical development process. The findings from the interviews then shaped the creation of a global survey. The survey was organized into four key stages of the innovation adoption process, namely, initiation, evaluation, adoption decision and full implementation (Figure 1).

Figure 1. The Biopharma Innovation Adoption Cycle

Survey methodology and data characteristics

The survey was primarly structured according to this four-step process with questions aimed at further understanding the process of adoption for new processes, systems and/or technologies that are transformative in terms of how the industry designs, plans, executes and manages data supporting clinical trials. Specifically, respondents were asked to consider innovations that are still emerging and haven’t yet reached industry-wide adoption. Illustrative examples were provided for reference and included eSource, eConsent, Risk Based Monitoring (RBM), Digital Health Endpoints and AI capabilities.

The survey asked respondents to characterize the timeframes for going through the various stages, the functional groups involved in the process, the types of quantitative and qualitative information used to advance from one stage to the next along with key challenges and barriers associated with each stage. Broader questions related to perceptions about how companies fared in their innovation adoption approach compared to others, and about how respondents viewed their company across the innovation diffusion model—innovator to late adopter or laggard—were included. The survey also captured perceptions of how the pharmaceutical industry compared to other industries when it comes to speed of innovation. Finally, the survey focused on opportunities for accelerating the innovation adoption process.

A total of 552 responses were received from a global audience primarily representing pharmaceutical and biotechnology companies. Approximately six percent of the respondents were from CROs or other organizations; however, responses from these individuals were not included in the primary analyses. Just over half of the respondents (53.9%) worked across large sponsors with 28% working at mid-size companies and 18.1% at small biopharma.

Nearly half of responses (49.3%) were received from individuals whose company headquarters were in Europe. 38.8% and 12% of responses were received from respondents with company headquarters based in North America and Rest of World (ROW), respectively.

A variety of roles were also represented, including professionals from Clinical Operations (46%); Clinical Development (9%); Innovation Management (17%); Data Science & Data Management (10%); Information Technology (3%) and 15% from other roles. About half (51%) of respondents reported that they had some influence on the adoption decision making process, with 30% indicating they had little to no impact on the decisions. 19% of respondents indicated that they were key decision-makers when it comes to the process of pursuing, evaluating, or implementing innovations in their organizations. Finally, 14.5% of respondents were part of a centralized or dedicated innovation group whereas the majority (85.5%) worked outside of such an innovation group.

Over two-thirds (69%) of respondents indicated that the adoption process within their organization generally followed the four-step approach as outlined above (Figure 1). Where the process differed, respondents indicated that there was no formal process, or that certain steps were less defined or skipped altogether. Interestingly, some respondents from smaller companies reported having staff with experience at large companies where things were “overprocessed”, and have therefore made the decision to eliminate the process altogether. These companies intentionally decide to move straight into implementation, preferring to sort out issues along the way rather than formalizing the method and/or metrics by which they evaluate and implement an innovation.

Thus, responses reflect a broad crosssection of views and perspectives from which to learn more about how the biopharmaceutical industry approaches the innovation adoption process, what gets in the way and how organizations, and the industry more broadly, can accelerate new technologies and innovations.

The survey results revealed that within individual biopharmaceutical companies the average innovation adoption cycle for a given clinical operations innovation lasts about 6 years. The longest reported cycle lasted 10 years with the shortest lasting 1.5 years (Figure 2).

Figure 2. Average Duration of Stages in the Biopharma Company’s Innovation Adoption Cycle

Cycle times varied by company size. Small biopharma reported the fastest cycle times and mid-size companies reported the longest (Figure 3).In general, the time to complete each stage increased across the four stages with the initiation step being the shortest and the full implementation stage taking the longest. The high coefficient of variation (CV) suggests wide variation in the length of each stage of the innovation adoption cycle.

Figure 3. The Biopharmaceutical Innovation Adoption Cycle by Company Size

When it comes to the impetus to pursue or explore an innovation, the results suggest that the primary factors are (1) a new or updated regulatory guidance, (2) an operating objective to improve the speed of clinical development, or (3) a mandate from senior management to pursue an innovation (Figure 4). The support and advocacy of senior leadership along with regulatory compliance and approval considerations were also big drivers of the decision to progress to the next stages. Financial considerations were among the top three drivers during the evaluation, adoption decision, and full implementation stages. The presence of change management strategies played a key role in the decision to move forward with full implementation.

Figure 4. Key Factors Driving the Progression of Stages in the Innovation Adoption Process

When asked about barriers and challeges, study participants reported that the easiest stages to complete were the earlier stages of the process (initiation and evaluation) with the adoption decision and full implementation stages being the most challenging (Table 1).

Table 1. Perceived Difficulty of Stages in the Innovation Adoption Cycle

Some interesting themes emerged in the analysis of barriers to completing or advancing to the next stages of the innovation adoption process. Key themes include:

Specifically, employee turnover and lack of cross-functional alignment are key factors that play a role across most stages. The lack of senior management involvement and support was identified as a key barrier at the evaluation and full implementation stages.

The lack of regulatory clarity and need for legal review and approval of the given innovation were reported as barriers across all stages indicating that companies like to ensure legal and regulatory acceptability prior ot moving to the next stage.

Financial constraints were noted as barriers in the three later stages, but were not reported as an issue impacting the initial pursuit of a potential innovation. Interestingly, the misalignment of incentives was also noted as a key barrier through the three later stages as well. This comes in the form of lack of rewards or recognition for exploring and advancing new ideas and the perceived risks associated with not meeting deadlines or budgets.

During the evaluation and adoption decision stages, difficulties in comparing vendors and uncertainty about the viability of a given vendor factored more heavily into the process to advance to the next stage, compared to vendor related considerations in the initiation or full implementation stages.

The absence of change management strategies and planning were identified as important challenges at the beginning and end stages of the process.

Opportunities to accelerate adoption of innovations

Many of the challenges and barriers noted by study participants are actionable.While there is recognition that greater regulatory clarity would be helpful in accelerating the process, this is often outside the direct influence of senior leadership (but something that regulatory agencies could do to facilitate more rapid adoption of new innovations). Nonetheless, respondents identified many opportunities for improvement in areas related to personnel, finances and incentives, and operations.

Senior leadership’s presence and support throughout the process

The most striking finding is that visible senior management support and promotion of an innovation throughout all stages of the process can lead to its faster adoption. Repondents echoed the signifincance of senior leadership mandates—as well as their presence and engagement at all stages—in improving the speed of innovation adoption. These perceptions align well with the correlations observed between companies with shorter timelines and the presence of senior leadership at each stage of the adoption cycle. Those companies that had senior leadership involvement at all stages also showed shorter timelines compared to those without. The mandates and support of senior leadership, coupled with the establishment of operational objectives to improve the speed of clinical development, can lead to shorter adoption cycles.

It is important to note that active, visible involvement and encouragement by senior leadership is currently a key factor in the speed of innovation adoption because the decision-making power on matters that affect innovation adoption tends to reside exclusively with this select group. An alternative approach that has been looked at, particularly within larger organizations, and which warrants further investigation is one where this decision-making power—and the accountability that follows it—is adequately distributed among teams and individuals throughout the organization.iv This approach could offer companies the ability to adapt easily, and to quickly make decisions that directly impact the speed of innovation adoption.

In a similar vein, company leadership are encouraged to continue to develop a culture of innovation within their organizations and across industry. Our research showed that nearly half of the respondents (42%) indicated either high or moderate risk to their performance review when pursuing adoption of an innovation. Thus, leaders are encouraged to build incentives for participating in the innovation adoption process into individual performance reviews.Offering incentives and recognition for the pursuit of a new approach instead of only holding individuals accountable for adherence to study timelines and budgets tends to be correlated with higher satisfaction with the innovation adoption process within biopharmaceutical companies. Providing adequate funding, resources and financial incentives to these individuals so that they can explore, pilot, and drive the adoption process can lead to quicker innovation adoption timelines. Additionally, leaders should be mindful of inadvertently penalizing individuals who develop, champion, and/or try new ideas, approaches and technologies.

Another important element for the development of a culture of innovation is the presence of a change management strategy. Study participants reported that change management strategies and communication planning play significant roles in fostering faster adoption. Waiting for the full implementation stage to think through how the organization will use, integrate, and manage a given innovation may hamper its rapid adoption.

An important outcome of this research is that substantive differences in cycle times were not identified between companies that have a dedicated innovation group compared to those that don’t. Intuitively, the presence of a dedicated innovation group would lead to faster cycle times or fewer challenges in the later stages of the process; this hypothesis was not validated here, however. Interestingly, respondents from smaller biopharma companies suggested in high proportion that innovation groups could help accelerate the adoption process. These were also the same companies that reported the presence of innovation groups in the lowest proportions compared to mid-sized and large pharma, while reporting the fastest timelines. The faster timelines observed at smaller biopharma might be explained by their greater reliance on CRO partners, the smaller scales in which they work, and their high degree of specialization in one or few therapeutic areas, among other factors. This topic warrants further investigation and is an area that we hope to explore further in future research.Based on our extensive review of examples in the literature, the stages of the innovation adoption process, and the durations and challenges, are consistent with those encountered by similar, highly regulated, research intensive industries.

The industry may be missing out on key opportunities to accelerate drug development through a lengthy and inefficient process for evaluating and adopting innovations. Cross-company collaborations, partnerships with CRO and vendor partners, and regulatory guidance and clarity can support broader industry-wide adoption of innovations.We recognize that the rapid adoption of DCT solutions during the pandemic was facilitated in part by unprecedented proactive and accommodating regulatory agency involvement

At the company level, this research found that full implementation of a new technology or process in clinical operations can be achieved in under two years. Through mandates, senior leadership involvement, cross-functional engagement, financial support, better alignment of incentives, and improved change management and planning, biopharmaceutical companies can be more proactive and intentional about the way they explore and pursue innovations.

We would like to acknowledge the study’s Working Group for their contributions to this research.

*In this research we are defining “wide-adoption’ as approximately 70% of industry having decided or being in the process of fully adoping the technology or capability.

https://www.outsourcing-pharma.com/Article/2020/10/29/NoGoingBack-mission-brings-trial-pros-together

Tufts CSDD Analysis, presented at Veeva R&D Summit, June 10 2019, Barcelona, Spain

Tufts CSDD White Paper – Adoption of Innovative Technologies within Pharmaceutical R&D, May 2020

Articles

Characterizing the long-term adoption experience of clinical technologies and capabilities—and what senior leaders can do to drive adoption within their walls.

Accelerating Innovation Adoption to Support Drug Development Operations

During the pandemic, patient engagement (e.g., participation convenience, safety, research relevance, ease of use) has been a guiding principle in the transition to remote and virtual clinical trial support. Given the high level of customization inherent in decentralized and hybrid clinical trial execution models, a growing number of sponsor companies are now looking in earnest to quantify the impact of patient-centric initiatives. Although the Tufts Center for the Study of Drug Development (CSDD) and others have dedicated considerable time and attention to gathering objective evidence, until recently, very little has been available.

Several years ago, the Drug Information Association (DIA) and Tufts CSDD analyzed 121 distinct case studies to quantify the impact of patient-centric initiatives. In this early study, patient engagement initiatives that offered the highest impact given the investment required were patient advisory boards, professional panels, social media engagement, and patient education programs. These initiatives were relatively simple to implement and inexpensive, yet they reportedly resulted in faster study planning, improvements in recruitment and retention rates, fewer disruptions and delays, and more positive study volunteer feedback. Unfortunately, there was too much variability in definitions, types, and quality of the metrics collected across case examples. As a result, return on patient engagement could not
be generalized.

In another study, Tufts CSDD—in collaboration with the Clinical Trials Transformation Initiative (CTTI)—developed a method for projecting the financial value of patient engagement using standard risk-adjusted financial modeling techniques. The CTTI-CSDD team assessed the impact of patient engagement on the expected net present value (ENPV) for a typical oncology development program entering Phase II or III clinical trials. For a Phase II project, the cumulative impact of a patient engagement activity (e.g., patient advisory board review) that avoided one protocol amendment and improved enrollment, adherence, and retention was an increase in NPV of $62 million, rising to $65 million by Phase III, and an increase in ENPV of $35 million, increasing to $75 million by Phase III. Depending on the scenario, a $100,000 investment in a patient-centric initiative during the design of the study could produce NPV and ENPV 500 times that amount. This ENPV increase is equivalent to accelerating a pre-Phase II product launch by 30 months or 18 months for a pre-Phase III project.

During the past 24 months, Tufts CSDD has undertaken several new studies to gather more objective and practical evidence quantifying the impact of patient engagement. Sponsor focus of late has been particularly high on protocol design given the fundamental role it plays in directing downstream clinical trial activity. Sponsors expect that the ability to incorporate patient preferences and needs during the protocol authoring and finalization period offers a unique and unprecedented opportunity to optimize study design and positively impact clinical trial performance and cost. The results of two CSDD studies underway inform this area.

Patient advisory boards (PABs) usually entail soliciting feedback from a group of patients and their caregivers (e.g., patient advisory boards or input panels) on the feasibility and convenience of near final protocol designs. PABs are typically moderated meetings among six to 10 people. Although they are not enrolled in clinical trials, participants in an advisory board usually share the burden of disease investigated by the protocol permitting them to speak from direct experience. At this time, an estimated two-thirds of the top 50 largest pharmaceutical and biotechnology companies have implemented one or more PABs to obtain specific protocol design feedback.

To assess the impact of PABs, Tufts CSDD has analyzed data from a convenience sample of Phase II and III protocols conducted between 2015 and 2019 across multiple therapeutic areas. Of 153 protocols analyzed, 12 utilized PABs. Given this small sample size and the wide variation in disease conditions represented, these results should be interpreted with caution until a more robust sample has been analyzed.

PAB input resulted in simpler protocols and more targeted designs compared to those that did not receive input. PAB-informed protocols had, on average, fewer endpoints, eligibility criteria, and distinct procedures.

The number of procedures performed per visit and the total volume of data collected per patient was significantly lower for PAB-informed protocols. Protocols informed by PABs had an average of 15 endpoints and 27 eligibility criteria, 30% and 20% less, respectively, than did protocols that were not informed by PABs. Protocols that used a PAB for design input collected 2.2 million data points, 50% fewer than protocols that did not receive PAB input. And PAB-informed protocols had a lower percentage of procedures supporting tertiary and miscellaneous endpoints.

The results also indicated that protocols receiving PAB input had better relative performance and efficiency. Notable differences between protocols informed by PABs and those that were not informed include faster study initiation, shorter clinical trial duration, quicker study close-out, lower-than-planned study budgets, and fewer average number of substantial protocol amendments.

The actual cycle times of protocols that did not use PABs typically exceeded planned timelines by between 20% and 90%. Actual cycle times for PAB-informed protocols came in closer to plan (e.g., study initiation cycle time) or beat the plan time lines by 6% to 17%. And actual PAB-informed protocol budgets came in 28% below planned budgets. Protocols that did not use a PAB tended to have actual budgets 3% above plan. Protocols that used a PAB had on average one fewer substantial amendment than those that did not.

The use of a patient burden assessment score or algorithm has been gaining momentum as valuable input into early-stage protocol authoring. A tool developed by the National Institute of Health several years ago measured patient attitudes and correlated them with patient self-report of the likelihood to participate in, and the intent to drop out of, a clinical trial.

Dassault Systems and IQVIA have been developing and beginning to pilot-test patient burden assessment tools (e.g., the Patient Burden Index and the Patient Friction Coefficient, respectively) among pharmaceutical companies.

In 2019, Tufts CSDD—in collaboration with ZS, a global management consulting firm, developed and tested an initial participant burden algorithm against pharmaceutical and biotechnology company protocols based on the perceptions and preferences of 591 patients living with one of five disease conditions in the US.

During the past 14 months, we’ve compiled overall and clinical trial-specific preferences and perceptions from 3,002 global patients across 39 disease conditions to derive and test a revised algorithm against a convenience sample of 266 recently completed protocols. This algorithm takes an expansive look at participation burden and includes protocol procedures, clinical trial logistics and convenience, disease burden, medication adherence, mobility, lifestyle restrictions, and caregiver reliance.

The revised participation burden algorithm is highly associated with, and predictive of, many clinical trial performance outcomes. Mean participant burden scores were highly correlated with, and predictive of, screen failure rates. This result is consistent with past qualitative studies that have demonstrated the impact of perceived burden on reducing patient willingness to enroll in clinical trials.

Mean participant burden scores were also positively correlated and predictive of treatment duration and overall clinical trial duration. These two cycle time measures are in part a function of the long-term effects of protocol demands on participant retention.

Burden scores were not predictive of study start-up (approval to FPFV) or study close-out (LPLV to database lock) durations. These latter two cycle times are less dependent on study participant experience and more dependent on clinical research professional preparedness, coordination, and efficiency.

We were disappointed to find that our enhanced participant burden score was not associated with, or predictive of, clinical trial drop-out rates. We used a broad definition of “drop-out rates” in the study that included all factors other than volunteer mortality. For this reason, drop-out rates were a function of far more than the volunteer’s decision to prematurely terminate participation. Drop-out rates included administrative factors; lack of efficacy and insufficient therapeutic response; drug safety issues and adverse events; study-specific withdrawal considerations (e.g., pre-defined discontinuation considerations and volunteers no longer meeting the study requirements); and poor compliance and protocol non-adherence.

In future applications and assessments of the participation burden algorithm, we plan to focus on drop-outs specifically associated with protocol demands and inconveniences resulting in premature termination of participation. New research is underway to apply the participant burden algorithm prospectively in protocol design. Ten pharmaceutical companies are working with Tufts CSDD and ZS to benchmark mean participant burden scores across protocols in their portfolio. Retrospective company participant burden benchmarks will be used to guide prospective protocol authoring.

The insights from these recent studies and ongoing research are intended to assist drug development teams and protocol authors in leveraging patient voices to retrospectively understand clinical trial performance outcomes and to prospectively inform protocol design decisions.

Looking beyond protocol design, Tufts CSDD and the DIA are also embarking on a new working group study in the fall of 2021 to gather robust, objective, and practical data linking organization-specific patient engagement initiatives—pre-, during and post-participation—to clinical trial and program-level performance and quality outcomes. We encourage sponsor organizations to participate.

Insights from studies on advisory boards and participation burden.

Amplifying Patient Voices in Protocol Design

Remote and virtual clinical research team collaboration has been a defining characteristic of global drug development activity during the pandemic. This article, based on research conducted between September 2020 and April 2021, summarizes how organizations approached adapting to remote operating models and the associated experiences and effectiveness of clinical research professionals managing their roles and responsibilities.

The goal of this article is to provide insight into lessons learned, and to guide considerations about the future of remote team collaborations within biopharmaceutical companies and other stakeholders in the clinical research enterprise.

The results reveal that drug development professionals have been mostly satisfied with their organizations’ remote preparedness and responsiveness and feel supported by their managers and organizations. In addition, clinical research professionals operating remotely during this global health crisis perceive that their productivity and effectiveness levels have been high, and the majority wish to continue to work remotely. The results also show that there are areas requiring attention: 55% of respondents reported feeling burned out and 42% reported that connections with colleagues had deteriorated.

Tufts CSDD research conducted early in the pandemic

 captured the variety of remote and virtual approaches being utilized. As expected, communication technologies—including video conferencing, cloud-based file sharing and telehealth—were the predominant approaches being used by clinical teams. Other widely used solutions—largely out of necessity—supporting clinical trial activities included eConsent and remote monitoring. 

A study conducted at the Cleveland Clinic Cancer Center

, revealed some key benefits of remote work and its impact on the execution of clinical research. The findings are based on analysis of productivity data sourced from a remote research coordinator (RC) pilot program that started one week prior to the onset of the pandemic. By March 25, 2020, all research coordinators at the Cancer Center were part of the program and working from home. The data collected revealed that the productivity and efficiency of RCs during at-home days was higher compared to in-office days. The program allowed for higher and better data entry, an increase in the number of trials initiated, and a reduction in trial times to initiate a trial compared to a similar time-period in 2019. An uptick in team morale was also observed. Nearly all members of the 60-person team expressed gratitude for their ability to work at home. Notable benefits included reduced stress and burden from commuting, parking, and fuel costs. Additionally, the work-from-home model correlated with reductions in team turnover.

Employee reports of productivity across industries during the pandemic have been extremely positive. Several studies suggest, however, that although organizations adapted well to remote operating models, many did not provide adequate communication and support. A study by Marsh McLennan among 256 employees, for example, found that one-third gave mixed reports of their manager’s preparedness and effectiveness in implementing company-wide response to the pandemic.

In another cross-industry study conducted among 5,043 full-time employees, high levels of anxiety were observed among personnel whose organizations did not clearly state their plans, policies and vision for remote work. The study, conducted by McKinsey & Company, also found that most employees would like to see their organizations adopt flexible and/or hybrid virtual working models after the pandemic has ended. More than 50% of participants in the survey would like to work from home at least three days per week in the future; those with young children are more likely to prefer fully remote working models.

Tufts Center for the Study of Drug Development collaborated with the Bill and Melinda Gates Medical Research Institute (Gates MRI) and undertook a global study in early 2021 to understand the attitudes, experiences and effectiveness of remote teams specifically within the clinical research enterprise. This study afforded the opportunity to gather more granular data and more targeted insights.

Tufts CSDD and Gates MRI teams established a working group of organizations comprised of stakeholders across the clinical research enterprise in order to solicit comprehensive and diverse input. A total of 26 organizations participated in this working group including representatives from patient advocacy groups, medical research foundations, academic medical centers, government agencies, pharmaceutical and biotechnology companies, contract research organizations and investigative sites.

Based on a working group discussion, a 69-question online survey was developed. In addition to questions assessing detailed respondent characteristics (e.g., demographics, organizational characteristics), the survey focused on specific steps taken to adopt remote work practices before and since the pandemic began, organizational support in the transition to remote work, employee wellness, capacity for work, diversity and inclusion, and the impact of remote approaches to work. Respondents were also asked about their perceptions surrounding clinical trial performance and the future of remote work.

Survey responses were fielded globally between January 27, 2021 and April 9, 2021. A total of 344

 unique responses were gathered and reflected high survey response completeness and variation.

 The results of our analysis are presented below. 

We analyzed twelve different subgroups (see Exhibit 1) to understand personnel experiences adapting to and operating remotely.

Exhibit 1: Characteristics of Respondents

Our sample includes respondents from more than 50 countries across five continents, as well as a wide range of races and ethnicities. More than half of respondents live in the US & Canada and self-reported white, female, and between the ages of 35 and 54. Most respondents also indicated having caregiving responsibilities and one or more children. Nearly six-out-of-ten respondents reported that they are employed by large organizations.

The vast majority of those working at academic medical centers and research institutions reside in the US and Canada.

Whereas some significant differences were observed across all twelve subgroups, significant differences (p

.05) were most commonly observed by organization type and geographic area.

Approximately four-out-of-ten (43%) respondents indicated that their productivity was unchanged since the pandemic began, while 35% reported that their productivity had increased. A lower proportion—19%—noted that their output had declined and 3% were not sure. Respondents working in pharmaceutical and biotechnology organizations were more likely to report higher productivity than respondents working in other types of organizations (p 

.05). US and Canadian respondents were more apt to report higher productivity levels since the pandemic began compared to European, UK, and Latin American respondents. Differences by respondent age were also observed; those between 35 and 54 reported higher productivity compared to respondents in younger or older groups (p 

Respondents’ self-reported assessments of their remote performance was high: 71% indicated ‘very effective’ and 26% ‘somewhat effective’. Similarly, more than three-fourths of remote team managers evaluated their teams as being ‘very productive’ (76%) and one-fifth (21%) as ‘somewhat productive’ since the pandemic began, reflecting alignment between the perceptions of team managers and individual team members (see Exhibit 2).

Exhibit 2: Self-reported remote performance vs. team productivity rating

Respondents from biopharmaceutical companies and contract research organizations (CRO) were more prone to report that they were either ‘very’ or ‘somewhat effective’ in their remote roles compared to those working at academic medical centers or research institutions (p

 .05). In addition, those without children tended to report that they were more effective (‘somewhat’ or ‘very’) doing remote work compared to those having one or more children. In comparing women and men, women had an increased likelihood of reporting that they were ‘very’ or ‘somewhat effective’ performing remotely compared to men (p 

The vast majority (93%) of respondents indicated they were satisfied with their organization’s preparedness in transitioning to remote work, 95% reported satisfaction with their organization’s responsiveness, and 57% reported satisfaction with provision of resources by their organization. European and UK respondents were more likely to report satisfaction with their organization’s preparedness and responsiveness (p

.05). In contrast, Latin American respondents were less likely to report satisfaction with provision of resources compared to those in other geographies. Individuals working at biopharmaceutical organizations were also more likely to report satisfaction with preparedness, responsiveness, and provision of resources when compared to other types of organizations (p 

Three-out-of-four (74%) respondents indicated that their organizations had a remote work policy in place prior to the pandemic and 66% reported that their remote work policies changed once the pandemic began. Some of the changes reported include financial support for better home office setups, allowance for relocation “beyond reasonable commute” areas, increased number of virtual meetings, and greater flexibility. In addition, respondents also reported increased quality and scope of information technology (IT) support, expansion of the existing remote policy to include roles that were previously not included, and a shift to permanently remote setups, among other changes.

A higher proportion of CRO respondents worked at organizations that had a remote work policy in place before the pandemic began. Biopharmaceutical respondents were more likely to say their remote work policy changed during the pandemic compared to other types of organizations (p 

A higher percentage of US and Canadian respondents reported that their remote work policy had changed since February of 2020 compared to respondents located in other geographies (p 

.05). Most respondents also reported that their respective organizations provided access to the basic elements of remote work such as laptops/desktops (89%), paid access to communications platforms (88%), and stable compensation (85%).

Notable differences were observed in levels of provision of resources by organization type, with pharmaceutical and biotechnology companies and CROs providing most resources to their staff at higher levels. Respondents from biopharmaceutical companies were more likely to report access to computer monitors and hardware such as mouses, keyboards, and headphones when compared to other types of institutions (i.e., non-profits, etc.) (p <.05). We found that a higher percentage of CRO respondents reported receiving paid access to high-speed internet compared to other types of organizations (p <.05). We also observed that higher proportions of respondents from academic medical centers, research institutions, and pharma/biotech companies reported access to updated standard operating procedures (SOPs) and regulatory compliance training during the pandemic.

Interestingly, significant differences were not observed in the importance rating given by respondents to each of the resources we enquired about. Most respondents agreed that paid access to high-speed internet and virtual communication platforms were highly important to the effectiveness of remote work, and yet these resources were not provided at similar levels across the various types of organizations included in this study.

Overall satisfaction with organizational approaches to remote work was very positive; 92% of respondents indicated they were ‘very’ or ‘somewhat’ satisfied with the approach implemented by their organization (see Exhibit 3). Respondents expressed satisfaction with their organization’s approach to cybersecurity (94%) and access to communication platforms (90%).

Exhibit 3: Satisfaction with organization’s approach to remote work since February 2020

Female respondents were more likely to be satisfied (95%) with their organization’s approach compared to males (90%). Biopharmaceutical companies and CROs were also more satisfied than were other types of organizations. These results were statistically significant (p 

Impact of remote work: burnout, inclusion, and social support

The Tufts CSDD/Gates MRI global survey also detected adverse effects of remote team activity. More than half (55%) of respondents reported feeling burnt out, while 9% of respondents said they were unsure. Burnout was primarily attributed to factors such as frequency of virtual meetings, added work responsibilities, restlessness, and uncertainty in work demands. The latter factor is consistent with findings reported in other recent studies.

Other factors contributing to burnout include feelings of loneliness and hopelessness, caretaking difficulties, and inadequate access to tools. Many respondents also reported facing emotional burden due to the US political environment in 2020, deterioration of co-worker relationships, and the inability to travel.

Respondents aged 18-34 were more likely to report burnout compared to those 35 and older (p 

.05). Female respondents were also more likely to report burnout compared to males—at 57% and 51% respectively (p value 

.05) A striking number of respondents within academic medical centers and research institutions—71%—said they have felt burnout since February 2020. This proportion is nearly 1.5x higher compared to respondents in biopharmaceutical companies, CROs, medical research foundations, patient groups, and government agencies. Not surprisingly, respondents who were in roles with frequent patient interaction were more likely to report feelings of burnout (61%) compared to those in roles without patient interaction (54%).

Among the 18-34 age group and those with caregiving responsibilities, the factors causing higher relative reported burnout included frequency of work-related meetings, added work-related responsibilities, uncertainty and variability in work-related demands, and feelings of hopelessness (see Exhibit 5).

Respondents in Latin America were almost 4x more likely to say that feelings of hopelessness were a major or moderate factor in their feeling burned-out compared to respondents in other geographies. Rest of world (ROW)—Asia, Australia, Africa—respondents were more inclined to report frequency of work-related meetings as a major or moderate factor in their burnout.

Exhibit 5: Differences in reported causes of burnout across age groups, geography, and whether they were caregivers

A high majority (82%) of clinical research professionals indicated that their feelings of connection to their colleagues had deteriorated since February 2020, with four out of ten saying they felt less connected to their colleagues. Loss of connection with colleagues was most observed among those in patient-facing roles (55%). Interestingly, 87% of survey participants said they felt somewhat or very supported by their colleagues, while 86% indicated they felt supported by their managers and leadership. Those working at pharmaceutical and biotechnology organizations were more likely to say they felt supported by colleagues, managers, and leadership, compared to those employed by academic medical centers and research institutions (p <.05); 90% of respondents from biopharmaceutical companies reported feeling supported compared to 82% at academic medical centers and research institutions.

Eight-in-ten (80%) respondents reported that the greatest benefit of remote work and collaboration was increased flexibility followed by gained time from not having to travel or commute to work (12%). Better relative participation within and across teams was also a key benefit mentioned.

The vast majority of respondents (89%) felt that they were either ‘extremely’ or ‘somewhat’ likely to embrace adopting a mostly remote work model, and a similar percentage of respondents (84%) indicated a high probability that their organization’s leadership would accept continued remote work models (see Exhibit 6).

A mostly remote work model was defined as having 60% of staff working remotely at least 60% of the time. Females were more apt than males to support this model and US and Canadians were more prone to accept working primarily remotely compared to their European, UK, and ROW counterparts (p 

Exhibit 6: Likelihood of management to permanently embrace a ‘mostly-remote’ work model

Most respondents (86%) indicated support for their organization’s current remote model—or a similar version—to continue when the pandemic ends. Respondents over the age of 35 compared to other age groups; and females with one or more children at home were the most likely to support their organization’s current remote model after the pandemic ends (p 

Those in the US, Canada, and Latin America indicated support for their company’s remote work model compared to European, UK and ROW (Asia, Australia, Africa) respondents (p 

 .05). And pharmaceutical and biotechnology company representatives expressed a higher likelihood to want to continue in their organization’s current remote work model compared to those working in other organizational settings (p 

The results of the Tufts CSDD/Gates MRI Remote Clinical Research Team Experience and Effectiveness study indicate that clinical teams have transitioned to remote collaboration models well facilitated by employers who are generally supportive and prepared. Remote clinical teams report performing their roles effectively, but a high percentage are feeling burned out and experiencing deterioration in their connections with their colleagues. 

Gaps were identified in respondents’ perceived importance of resources in select areas compared to organizations’ provision of these. Wide gaps were especially seen in the perceived importance of high-speed internet access and external computer monitors compared to their provision, suggesting that additional investment may be required by certain organizations in select areas to sustain their remote work activity.

Biopharmaceutical company and CRO respondents reported a greater likelihood of perceived effectiveness in their remote roles compared to those working at academic medical centers or research institutions. This result may also be tied to (1) differences in investment in resources at other types of organizations, and (2) that academic medical centers and research institutions may require greater support from sponsors and other stakeholders to conduct clinical research effectively using remote approaches.

Global differences also were observed in self-reported productivity; respondents in the EU, UK, and Latin America reported lower levels compared to their counterparts in the US and Canada. This finding suggests that there may be geographic disparities in the level of remote support provided. Further study is needed to examine this area. 

Substantial burnout was observed globally with the primary causes identified as frequency of virtual meetings, added work-related responsibilities, variability and uncertainty and feelings of restlessness. Younger workers, women, and respondents from academic medical centers and research institutions were more likely to report burnout. Retaining younger workers could become a greater issue as the pandemic ends with those workers leaving for organizations that return to the workplace or offer more opportunities to interact and collaborate face-to-face with co-workers. In addition, workers who were younger than 35 were also less likely to endorse a remote model in the future. Women, however, were more likely than men to support a future remote model, suggesting that more support might need to be established for women who continue to work remotely to avoid experiencing burnout. More effective and less frequent virtual communication may help address burnout while improving connectivity among workers.

Despite some of the subgroup differences, the vast majority of respondents support a version of their organization’s remote model when the pandemic ends. This finding underscores the importance of establishing operating models that can accommodate a variety of options simultaneously for employees who prefer to continue to work from home and those who prefer a mix of home—and office—based activity, especially younger workers and women. Offering flexibility to those who have responsibilities outside of work is critical and has been characterized in other studies.

The Tufts CSDD/Gates MRI study focused on the impact of remote clinical team collaboration experience at the beginning and in the earlier stages of the pandemic. We will continue to examine and draw lessons and insights on remote team experience and effectiveness long after the pandemic is behind us. As organizations adjust and adopt policies to accommodate and support a global remote and hybrid workforce, newer models and opportunities to drive innovation and employee satisfaction will no doubt emerge.

, MBA, is Deputy Director and Research Professor; all of Tufts Center for the Study of Drug Development, Tufts University School of Medicine.

Alexander, De Smet, Langstaff, Ravid. What employees are saying about the future of remote work. McKinsey and Company Report. April 1, 2021. 

Cleveland Clinic’s Cancer Research Team Sees Increased Productivity During COVID-19. Cleveland Clinic. December 7, 2020. 

Jenkins, Zabor, Mooney, et al. Increased Productivity and Efficiency Among Cancer Center Clinical Trials Workforce during the COVID-19 Pandemic. 

LeBreton, Lamberti, Dion, et al. COVID-119 and Its Impact on the Future of Clinical Trial Execution. Applied Clinical Trials, October 22, 2020. 

Caputo, Hyland. Employee Concerns about COVID-19. Marsh McLennan Report. 2021. 

344 surveys were submitted with fully signed and completed consent forms.

For nearly every question, approximately 15 respondents chose not to answer.

A summary of how organizations approached remote operating models and the experiences and effectiveness of clinical research professionals in their roles and responsibilities during the COVID-19 pandemic.

Remote Clinical Research Team Experience and Effectiveness During the COVID-19 Pandemic

Throughout the pandemic, clinical research stakeholders have been both amazed and immensely proud at the collective effort to adapt and address a monumental global health crisis in record time.

A great deal has been written and said about the factors that have contributed to the delivery of COVID-19 vaccines more than five years faster than typical development timelines and to the more than 1,000 COVID-19 treatments and vaccines now in the pipeline. The top contributing factors include:

The proactive and accommodating way that regulatory agencies and ethical review committees have supported development planning and activity.

The rapid mobilization of internal and external scientific and operating teams with a singular and common focus.

The fast deployment of remote and virtual technology solutions supported by more open data, information sharing, and advanced analytics.

The execution of parallel clinical trials and the compressed time between clinical trial phases.

The de-risking of development activity through the availability of global funding and resources.

The unusual frequency and extent of global media coverage contributing to unusually high public visibility.

The clinical research enterprise has much to celebrate, especially in light of the fact that most adaptations and changes represent a major departure from normal operating conditions. Many of the approaches and solutions deployed—such as remote monitoring, e-consent, home nursing visits, and integrated data management platforms—faced significant difficulty replacing legacy approaches before the pandemic. Many were stuck in planning or piloting stages for decades.

There is now substantial speculation about how the clinical research enterprise will function when the pandemic is fully behind us. How will the enterprise apply and embrace the experiences and lessons learned during this unprecedented period? Beginning in late 2020, articles, podcasts, webinars, and conference presentations began surfacing, most with both wishful thinking and pledges not to return to pre-pandemic operating conditions.

In recent months, we have learned more about underlying conditions that have supported pandemic response and a clearer picture is emerging of issues and challenges that will contribute to some retrenchment and more conservative application of adaptive and innovative practices as we move into a post-pandemic world. Two recent Tufts Center for the Study of Drug Development (Tufts CSDD) studies help paint that picture: the first study is an in-depth collection of interviews with principal investigators and senior study coordinators from the global community of investigative sites and site networks. The second study is a global survey—conducted in collaboration with the Bill & Melinda Gates Medical Research Institute (Gates MRI).

Tufts CSDD conducted a total of 26 in-depth interviews during March and April 2021, approximately one full year after the international community began locking down and clinical trial activity abruptly shifted to remote monitoring and decentralized support. Investigators and study coordinators noted several positive outcomes. The majority pointed to sponsor company and regulatory agency responsiveness and encouragement of adaptive practices as critical success factors. Site professionals felt that the most positive outcome in the transition to virtual and remote clinical trials has been the increased choice and accessibility offered to patients considering participation and the substantial improvement in study volunteer convenience.

But with few exceptions, the global community of investigators and study coordinators indicated that operating remotely and virtually has greatly increased workload for site personnel. Many noted the inordinate amount of time they have dedicated to learning new technology solutions; providing support to remote monitors and health professionals; training vendors unfamiliar with the clinical research process; and coordinating and integrating disparate and fragmented activities. Most interviewees pointed to significant delays that they have encountered starting up studies, receiving clinical trial supplies and lab kits.

Many conveyed concerns about the delays they experienced in receiving payments to help defray the substantial upfront risk sites assumed in supporting modified and adapted execution models.

In nearly every in-depth interview, investigative site personnel discussed the wide variability in approaches and solutions deployed by sponsors and contract research organizations (CROs) that contributed to high levels of uncertainty and the increased potential for errors and mistakes.

Between mid-January and April 2021, Tufts CSDD and Gates MRI gathered 344 global responses primarily from pharmaceutical, biotechnology companies, and CROs. The purpose of this online survey was to assess the experiences and effectiveness of development teams operating remotely. Two-thirds of respondents are employed by major and mid-sized companies and a similar percentage reports having team management responsibility within clinical, data management, and clinical operations functions.

Overall, respondents reported very high levels of productivity while operating remotely. Nearly all (97%) indicated that they can perform their role as a remote employee “very effectively” or “somewhat effectively.” But more than half of respondents (55%) report feeling burned out and 42% report that connections with their colleagues have deteriorated.

Factors contributing to burnout are intuitive and generally familiar to us all. The top three included the frequency of virtual meetings (by 67%); increased workload and additional responsibilities negatively effecting life balance (65%); and the emotional impact of dealing with uncertainty and isolation (54%). Unaddressed, it is likely that the feelings of burnout and loss of connection will continue to rise.

In open-ended responses, several indicated that the inability to travel and meet face-to-face with colleagues detracted from their collaborative effectiveness. Several also noted the challenges of not having a clear sense of the return on investment (ROI) for various solutions deployed and of the higher relative start-up cost and time investment required to support decentralized clinical trial activity.

Despite these experiences and concerns, the vast majority of respondents want to preserve their ability to operate remotely: 86% want their employer to continue offering “mostly remote” work when the pandemic is over; 6% indicate that they are uncertain about what operating model they want in place; and 8% said that they do not want their organizations remote operating model to continue.

We plan to publish the full results of the Tufts CSDD–Gates MRI study in 

Pandemic experience and response has exposed drug development organizations to numerous possibilities that would not have otherwise been widely adopted. Many observers would argue that this unusual adoption experience is not a reflection of a new standard operating environment but rather a one-time occurrence—a grand pilot program—providing a unique opportunity to consider, integrate, and apply “suitable” new options and choices.

Once the pandemic is behind us, these options and choices will likely be offered simultaneously with other more traditional approaches to balance and best satisfy study volunteer preferences, convenience, and scientific and operating requirements. Ultimately, these more expansive hybrid approaches will increase clinical trial complexity and customization, resulting in well-known outcomes: inefficiency, poorer quality, slower timelines, and higher costs.

Given cultures that have historically been risk-averse and resistant to change, many sponsor companies and their CRO partners will step-up efforts to scrutinize capital, personnel, and resource investment in, and double down on challenging, newer innovative practices. For the majority of organizations, it is likely that the pendulum will swing back toward slower, more measured response and more
limited acceptance.

A minority of organizations—those willing to take more risk—are already applying the implications of pandemic experience. Many are evaluating ways to better support teams operating remotely with more variable, agile, and flexible staffing models, infrastructure, and standard operating procedures. Several have shared the intent to consolidate their fixed, physical operating footprint, to continue to reduce study participant burden, and to entertain more open collaboration models.

Clinical research data volume has been rising dramatically for decades as protocol design objectives and scope have increased. The diversity of sources for clinical research data—including specialty labs, mobile and wearable devices, and patient health records—has also intensified. Post-pandemic, the juggling of highly customized clinical trial executional models will drive the collection of more data informing operating performance, efficiency, and quality. This rapid expected growth in rich data volume cannot be managed by traditional means alone and will rely more heavily on sophisticated and augmented analytics, including machine learning, risk-based quality management, and risk-mitigation techniques.

As the pandemic recedes and we gather more robust data on its full impact, we can anticipate wider variation in sponsor, CRO, and investigative site operating strategies and practices.

We will look back at our collective response with not only amazement and pride but also the knowledge that the pandemic did not solve our perennial drug development operating conditions. Rather, it necessitated experiences that affirmed, informed, and elevated enterprise-wide commitment to patient engagement and digital transformation.

Affirming and advancing patient engagement and digital transformation.

Contemplating the Full Measure of Pandemic Response

The drug development enterprise is undergoing a transformation of great magnitude driven by the cross-industry digitization of product development and the rise of Big Data. In 2020, we witnessed the acceleration of this evolution due to challenges created by the COVID-19 global health crisis. Out of necessity, the drug development sector is now embracing technologies and digital methods that were previously not as widely used. The sector is being forced to adapt to a new normal characterized by the maturation of data management solutions, an expanded number of data sources, and the unprecedented increase in data volume.

The sources of information and data management solutions that support drug development have evolved considerably over the past 40 years. During the 1980s and 1990s, clinical development focused on the gathering of small scientific data sets that yielded limited insights. In comparison, during the first two decades of this century, the enterprise gathered not only scientific data, but also collected operational data to improve the product development process. The sector’s use of data continues to evolve into what is now a nascent patient-centered data driven system that requires flexible models supported by augmented analytics and machine learning. These methods are expected to support an increasingly decentralized, predictive, and personalized drug development process.

The continued contribution of the drug development community toward improving the quality of lives of patients, researchers, and the public at large, is and will continue to be highly dependent upon the careful execution of strategies to make vast amounts of data meaningful and usable. This is achievable by pairing data with powerful analytics and then using those insights to develop safe and effective processes and products.

Although the drug development enterprise is undergoing major transformation, literature about what the sector should do to support and prepare its workforce for these changes is scant.

What follows is a discussion of original research conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD) to address workforce development in the era of digitization. The research is primarily based on an in-depth discussion with thought leaders and senior executives. Tufts CSDD identified recurring themes for discussion in articles in academic journals and the trade press between 2015 and 2019. Discussion topics included: (1) challenges and opportunities caused by the sector’s digital transformation, (2) skills and competencies of future drug development professionals, (3) new roles that are expected to emerge within drug development, (4) changes in talent recruitment and retention practices, and (5) the reshaping of corporate mindsets and cultures to become digitally proficient organizations.

In December of 2019, Tufts CSDD moderated an in-person discussion in New York City among 60 executives from pharmaceutical and biotechnology companies, technology solutions companies, professional trade organizations, and academia. Their functional expertise included clinical research, clinical operations, data management, regulatory affairs, human resources, digital technology, and R&D strategy.

Participants first discussed how digital transformation and patient engagement have changed the nature of clinical and operational data. Industry now prioritizes the collection of patient-centered data in addition to scientific and operational data. This new emphasis on patient-engaged science is facilitating an open, customized, and predictive framework for drug discovery and development. But patient-engaged science also leads to even larger data volume; this requires wide-spread knowledge of advanced analytics, cross-platform accessibility, continuous and flexible learning, and effective leadership within and between organizations and regulatory bodies.

Trends shaping the digital transformation of the drug development enterprise

The global labor market has been experiencing widespread changes over the last decade, and the drug development enterprise has been undergoing a dramatic transformation of its own. The speed of digital innovation is leading to accelerated creation and destruction of jobs within organizations. One expert roundtable participant noted:

“Lines are blurred. New positions are developing. Existing positions need to learn how to work with and interact with the new roles.”

As an example, in 2016, GEN News reported that the most in-demand biotechnology occupations were scientific in nature and included medical and clinical laboratory technicians, medical scientists, biomedical engineers, biological technicians, biochemists/biophysicists, and chemical technicians. By 2019, however, drug development’s most in-demand jobs were of a different nature and included statisticians, mathematicians, genetic counselors, operations research analysts, phlebotomists, medical and health service managers, and computer scientists.

 In only three years, the needs of pharmaceutical and biotechnology companies evolved from primarily “basic science” knowledge to “data science” skills. Because STEM skills are in high demand and have high employment multiplier effects, wages for STEM occupations are expected to increase pointedly over the next few decades.

The high demand for technical skills has also had important consequences for the supply side of the job market. The changing distribution of undergraduate areas of concentration highlights the impact. At major US universities, for example, computer science and statistics majors have been the fastest growing concentrations. At one major east coast university, the number of completed statistics and computer science concentrations increased 235% and 220%, respectively, between 2015 and 2017.

Clinical research and clinical care convergence

At the organizational level, decision-making is shifting from volume-based to value-based models. “Approximately 80% of hospitals in the United States are now facing outcomes driven metrics,” explained one roundtable participant. This newfound focus on value for patients requires the collection of accurate patient data. To collect these data, drug developers must resort to the existing infrastructure within clinical care processes, as well as partnerships with health systems, health data aggregators, online communities, and technology companies. The high cost of healthcare, coupled with the ubiquitous presence of mobile devices and digital healthcare applications, is driving people to become more engaged with their health and wellbeing. This change in behavior is generating vast amounts of actionable patient-generated data. As a result, more than thirty percent of data gathered is healthcare-related data.

The size and complexity of these data necessitates the use of artificial intelligence and machine learning to produce insights and accelerate problem solving. But these activities can only take place if the drug development workforce is nimble when working within existing clinical infrastructures and adept at integrating and analyzing data.

Higher demand for blended backgrounds and expanded skill sets

The drug development sector is embracing technologies and digital methods that were previously not as widely used due to the COVID-19 global health crisis. 