Benefits of R&D Collaboration

October 1, 2017

Applied Clinical Trials

Applied Clinical Trials, Applied Clinical Trials-10-01-2017, Volume 26, Issue 10

Learn to partner effectively in the era of collaboration, where the benefits gained will outweigh the challenges if approached correctly

Collaborations in clinical trials, or the clinical research enterprise as a whole, are not new. But in a recent survey with our partner SCORR Marketing, we found those collaborations are-and will continue to increase. 

In our survey, we delved into areas such as which types of collaborations are more
pervasive and those that are increasing; the benefits of collaborations, as noted in the chart at right; and the challenges, which included loss of control over project management, incompatible company cultures, legal or IP issues, lower than expected time, and cost savings.

In response to our question, “the rise in which of the following is the primary reason

for the upward trend in collaborative R&D arrangements,” the second and third answers were technology-related-big data at 27% and cloud technology at 13.5%. Clearly, technology is the backdrop by which all stakeholders in this survey-academia, biotech, contract research organizations (CROs), sponsors, research sites, and service providers can facilitate greater collaboration.

In this section, we present information on technology’s role in collaboration, from Jim Streeter, vice president of life sciences for Oracle, and strategy and management consultant Candice Hughes shares her views on the keys to improving and de-risking alliances and partnerships. 

- Lisa Henderson, Editor-in-Chief

Please download the free report here.

 

A Catalyst for Safer, More Efficient Trials

The emergence of cloud-based eClinical software is setting pharmaceuticals in good stead for significant progress. Cloud-based systems are well placed to unify disparate systems and enable pharmaceuticals to integrate each component of their drug development cycle into a distinct central database. This will help eliminate duplicate processes and allow different departments to work off a single and complete view of the data. This, in turn, can speed up the analytical processes of clinical trials, so that drugs can be brought to market faster. 

In addition, the better visibility of data that cloud-based software provides can speed up and enhance decision-making. For example, teams can more quickly prepare submissions for biostatistical analysis and share the lessons learned with the organization for future improvements. Take QuintilesIMS, the world’s largest CRO. The company offers its customers a real-time view of clinical trial data so it can evaluate progress and quickly adjust practices if needed. 

Cloud-based systems also provide efficiencies from a regulatory standpoint. With a clear view of where data is stored and how it runs between teams, organizations can process compliance reports or respond to health authority requests faster. 

Identifying new correlations 

Along with bringing efficiency to the drug development lifecycle, a more unified approach to data will enable scientists to discover new relationships in their data sets that could stimulate the creation of potentially life-saving therapies. 

One pharmaceutical company worked with PwC to uncover why a promising cancer treatment was failing in certain Phase III trials and to identify more appropriate candidates for future studies. Analyzing clinical and biomarker data from Phase II and Phase III trials helped attribute the therapy’s failures to a genetic imbalance in some patients suffering from the rapidly developing disease. As a result, the company was able to pinpoint several valuable biomarkers to help determine which patient groups to target and exclude in future trials. 

Opportunities with machine learning 

Collating, analyzing, and processing the entirety of a company’s data in a centralized way will also lay the groundwork for the success of technologies such as machine learning and artificial intelligence (AI), which will further enhance analysis. 

Although AI technology is still in its initial stages, we will see it being applied increasingly to help drive efficiency within pharmaceutical businesses. For instance, intelligent algorithms could automatically modify manufacturing capabilities to avoid product shortages by forecasting future supply and demand for new drugs.

AI also paves the way for more accurate candidate selection for clinical trials, working to reduce patient safety concerns. Analyzing data from the thousands of trials conducted will expose warning signals for potential safety risks. And as this data set expands, the level of insight it reveals will rise, and the probability of selecting at-risk candidates will decrease. Pharmaceutical companies are under a great deal of pressure to develop drugs faster while ensuring the highest levels of patient safety, and advances of this kind will be key to achieving this.

However, it will take more than technology to speed up clinical trials. To make the most of eClinical platforms, a cultural shift is also needed.

Research scientists have become accustomed to working in isolation for years, both due to the structure of their organizations and the limited technologies they work with. 

The transition to fully cloud-based eClinical platforms will require different approaches to working as well as more collaboration between teams throughout the drug development process. And with a collaborative culture, unified practices and a roadmap in place, pharmaceutical organizations will be well placed to accelerate and advance the nature of drug development in a significant, life-saving way.

- Jim Streeter, Vice President of Life Sciences, Oracle

 

 

Good Partnering Yields Value

A good example of the value of partnering is Novartis’s recently approved CAR-T therapy that was developed in collaboration with the University of Pennsylvania. With these and other successes, alliances are a necessity in the current market because the high cost of innovation means firms want to spread the risk through partnering. Besides risk, innovation requires an entrepreneurial culture that is far easier to grow and foster at an agile, smaller firm than it is at a large, global firm that may be risk adverse and focused on cost-cutting.

Partnering also is crucial for clinical trial operations involving outsourcing to universities, research hospitals, and CROs. While operating costs may be lowered, risks can potentially be increased, leading to costly regulatory and legal fines if partners are not carefully chosen and managed. 

While collaboration for innovation or cost-saving can be effective, there are a number of challenges that need to be overcome to ensure a partnership or alliance will be effective. In fact, these challenges are so strong that 60% of overall business strategic alliances fail, according to a recent CMO Council report. Failing partnerships cause employee stress and burnout. Great managers recognize the double-edged sword of alliances that are both critical to success and a danger with the potential for serious harm. The result of not assessing soft factors and choosing a poor partner negatively impacts firms in three critical areas: delayed or lost revenue, financial losses due to fines or lawsuits, and reputational damage. 

The one reason alliances fail

The key reason that alliances and partnerships fail is insufficient investigation and assessment of soft factors prior to and throughout the relationship. Soft factors include: corporate culture, alignment of goals, compatibility of alliance staff, similarity of processes or modification to suit the alliance, and clear and consistent communication, especially relating to goals and responsibilities. 

Along with these soft or human factors, partners need to perform strategic analysis to predict the most likely future situations that could impact the alliance, including goals and human factors. For example, while the partner’s goals seem to be aligned at the start of the alliance, what does each partner marketplace look like in three years? In five years? Will the goals be likely to remain aligned? Will staff turnover be elevated due to marketplace or other changes? 

While partners are used to and commonly check hard factors such as financials, technological specifications, cost-sharing, legal term agreement, and so forth, there is rarely an established process for checking soft factors, which are inherently difficult to assess.

Create a risk-based plan for assessment

On the positive side, pharmaceutical firms are well used to assessing and mitigating risk. It’s what they do day in and day out in their highly skilled regulatory departments or via other partners with expertise in this area. They or their partners can assess the risk failure overall or in specific areas respective to the firm. Once the areas of greatest risk with the partner have been identified, the firm can initiate a plan to perform de-risking due diligence.

Culture, for example, can be assessed via in-person observation, interviews, and surveys combined with analysis of online and media communications. A firm can conduct these types of analyses on its own. However, the company needs to be alert to bias and unintentional misdirection. First, it is hard to assess one’s own culture for the same reason that it is difficult to proofread something one’s written-it is hard to look clearly and carefully with no emotional or other bias at one’s self. A firm’s stated culture may differ from the day-to-day situation. Secondly, when people know they are being observed, especially by a potential partner, it is hard to avoid acting on one’s best behavior. Thus, the results should be weighted to reduce bias or misdirection or the assessments can be performed by an outsider. 

True short- and long-term goals can be determined by gathering the data through several approaches and assessed by comparing them to the most logical and probable goals for the situation. First, discuss goals with your potential partner. Those are the stated goals. Then examine goals provided via the media or other public information. From market research, competitor analysis, industry projections, and other data, probable and likely future goals can be determined. How do the goals match up? Even if they are not aligned, there could be a variety of reasons why. What is important is to assess how stated and projected goals match your firm’s goals. If there is misalignment, why, how much. and should further action be taken?

Key start steps

Communication is as critical as goal alignment and culture. Do the partnership teams have solid communication plans in place that have been agreed to by both sides? If not, this should be the first step for the new partnership. Along with the plans, should be clear responsibilities that don’t overlap. Additionally, procedures for frequent and regular status check-ins, along with milestones, should be defined at the beginning. The status discussions should not be rote, verbal “okay” confirmations, but should include checklists or completed work and next steps with appropriate confirmation of completed work. Partners could have differing views on completed work.

If the initial procedure setup does not go well, that is a clear sign that something was missed during the soft-factor due diligence and that should be revisited to determine where the partnership is going off course and how it can be resolved to get back on-course. 

When the due diligence process finds a problem area, the partners need to find a way to compromise or work around the challenge point. For example, if assigned personnel have strong incompatibilities, consider assigning a new team member. Even if they are less skilled functionally but a better fit personally, they may be able to work under or with the person with superior functional skills to gain that knowledge while enjoying a more harmonious partner team. 

Symptoms that a partnership is struggling include a sudden uptick in urgent emails, silence or complaints from the partner firm, and abrupt complaints to management that trickle down to the personnel on the partnership team (see chart below). Many of these issues relate to poor communication during the partnership, goals becoming misaligned over time, or inadequate initial due diligence. Getting to the true cause of the problem means there is a good chance of resolving it. A number of common situations and resolutions are included in the chart.

Appropriately de-risking the partnership up front, even given added costs, is the right approach to avoid much worse costs six months, a year, or a few years down the road. It is easy to want a partnership and overlook challenges or to want costs lowered right now and overlook more distant costs. Easy wins can be false wins. Success often comes from taking the harder path.

- Candice M. Hughes, PhD, MBA, Strategy and Management Consultant, Hughes BioPharma Advisers

 

 

    Next Page: Innovative Partnership Structures   

 

 

Alliance Examples

 

#1  Industry-Industry

Project Data Sphere-Global Oncology Big Data Alliance. The Global Oncology Big Data Alliance (GOBDA) is a recently announced joint alliance, co-led by Merck KGaA, Darmstadt, Germany, and Project Data Sphere, an independent, not-for-profit initiative of the CEO Roundtable on Cancer’s Life Sciences Consortium. GOBDA was formed to expand the open-access of de-identified patient data sets to further enhance analytical capabilities specifically for rare tumor patient data. The joint alliance builds on Project

Data Sphere’s current platform, which contains historical clinical trial data from almost 100,000 patients provided by multiple organizations. Leveraging these data on the platform with big data analytics will help to optimize clinical trials, build a registry of data, and help to enable advancement in the understanding of cancer treatment globally. In addition, by unleashing analytical power and big data to study and learn how to better manage rare but serious immune-mediated adverse events, institutes and industry will be able to assist regulators to adapt these new learnings into treatment guidelines, as well as establishing models to help enable early adverse event identification and improved patient outcomes. “The ultimate goal of our alliance with Project Data Sphere is to unleash the power of big data to bring value to cancer patients,” said Belén Garijo, member of the Executive Board of Merck KGaA, Darmstadt, Germany, and CEO of its healthcare business. The anticipated overall term of the GOBDA project and strategic collaboration will be from 2018-2021.

 

#2  Academia-Industry-Service Provider

BEAT AML Master Trial. Announced in October 2016 by the Leukemia & Lymphoma Society (LLS), the Beat AML Master Trial is a collaborative clinical trial for acute myeloid leukemia (AML). With guidance from the FDA, and LLS as the sponsor, the trial uses a precision medicine protocol that employs comprehensive genomic profiling to find and match specific AML genetic mutations in newly diagnosed patients over age 60, with an investigational drug or drug combination best suited to attack the specific 

molecular mutations causing the cancer. The trial started in February and LLS anticipates that 500 patients will be enrolled, with the study lasting from one to three years. As of July, six leading cancer centers have enrolled more than 70 patients, and four more institutions are expected to join the study this year. Four sponsors-Alexion, Boehringer Ingelheim, Celgene, and Gilead Sciences-are participating by offering investigational drugs, none of which are yet approved. At least three more pharma companies are expected to join the trial. Other collaborators include: Foundation Medicine, which  utilizes its proprietary genomic profiling assay for hematologic malignancies, for all of the patients; INC Research manages the logistics of the trial; Protocol First provides a web-based digital application to guide the clinicians; myClin provides a communications platform between the clinical trial sites for engagement and regulatory compliance; and Medidata’s Clinical Cloud solution will be used for data capture, management and reporting, and medical coding. 

 

#3  Academia-Government

I-SPY 2 Clinical Trial. I-SPY 2 is a partnership and collaboration between QuantumLeap Healthcare Collaborative (QLHC), Foundation for the National Institutes of Health, FDA, National Cancer Institute (NCI), 16 leading academic centers (researchers and physicians), the Safeway Foundation, and patient advocates. It is a standing Phase II randomized, controlled, multicenter study with an adaptive design aimed to rapidly screen and identify promising new treatments in specific subgroups of women with newly-

diagnosed, locally-advanced breast cancer (Stage II/III)-regardless of sponsors company. The innovative design utilizes biomarkers from each woman to assign her to a particular investigational drug. The trial learns as it goes, as each patient’s response to a particular drug informs how the next patient will be assigned to a treatment arm. Drugs with a strong efficacy threshold for a particular patient group may “graduate” to a more focused Phase III drug registration trial, while drugs found to be ineffective or with significant side effects are quickly dropped from the trial. I-SPY 2 graduate neratinib, from Puma Biotechnology, was approved by the FDA on July 17, as NERLYNX for the extended adjuvant treatment of adult patients with early stage HER2-overexpressed/amplified breast cancer, to follow adjuvant trastuzumab-based therapy. QuantumLeap was established in 2005 as a collaboration between medical researchers at University of California, San Francisco and Silicon Valley entrepreneurs to accelerate the transfer of high-impact research in clinical processes and systems technology into widespread adoption. 

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