Drug development in many diseases is now shifting toward molecularly targeted treatments that often rely on prognostic and predictive biomarkers for their application. Confronted with such major breakthroughs in the evolution toward personalized or precision medicine, the analytical and clinical validation of biomarkers and their eventual registration as 

 diagnostic devices (IVD) has received more attention recently. This article will provide a discussion around the need for integration of biomarker validation in clinical development, with a focus in oncology. It will highlight how flawed analytical and/or clinical validation can jeopardize a biomarker’s and drug’s clinical utility and showcase why biomarkers deserve statistical rigor throughout the development and validation process.

Precision medicine relies on validated biomarkers that allow classification of patients by their probable disease risk, prognosis, or response to treatment.

 Diagnostic biomarkers identify patients who are eligible for a given treatment due to the presence of a molecular alteration, such as mutation or gene rearrangement. A prognostic biomarker is used to identify the likelihood of a clinical event, such as disease recurrence or death. More relevant to precision medicine, predictive biomarkers distinguish patients who are likely to benefit from a given treatment, or conversely, to benefit from alternative treatments. A topical example in oncology is the presence of activating mutations of the epidermal growth factor receptor (EGFR); such mutations are associated with benefit from treatment with tyrosine-kinase inhibitors in non-small-cell lung cancer (NSCLC).

 Importantly, establishing that a biomarker is predictive generally requires a comparison against control treatment in individuals with and without the biomarker, usually in randomized trials.

The development and qualification of biomarkers are keys to the future of drug development and precision medicine, particularly in oncology. A validated predictive biomarker may become a companion diagnostic (CDx), defined by FDA as a medical device, often an 

 diagnostic device (IVD), which provides information that is essential for the safe and effective use of a corresponding drug or biological product.

 Moreover, integrating biomarkers into the therapeutic development process may allow less promising projects to be stopped earlier (especially before they enter into costly Phase III trials), thus optimizing the total cost of drug development.

A biomarker is only as good as the procedure used to measure it. Validation is the process of assessing the biomarker and its measurement performance characteristics and determining the range of conditions under which the biomarker will give reproducible and accurate data. Validation of a biomarker is a necessary component to ensure delivery of high-quality data necessary for effective clinical use of biomarkers. Biomarkers’ performance is evaluated at three different levels:

Analytical performance is the ability of a biomarker assay to measure the underlying biomarker quantity under a variety of conditions.

Clinical performance is the ability of the assay to inform about a clinical condition of interest.

Clinical utility is an assay’s ultimate ability to improve clinical outcomes.

The prerequisites for analytical validation are the unambiguous identification of the biomarker, the specification of the components of IVD (including the definition of a cut-off value when test outcomes are reported as positive/negative), and the definition of the context of use. With regard to the latter, the results obtained with the IVD should be “reliably correct”, and the validation process should be “fit-for-purpose” (i.e., the analytical performance of the CDx is suitable for the intended clinical use). Typically, companion diagnostics make the distinction between biomarker-positive and biomarker-negative individuals (so called “qualitative tests”) based on a cut-off applied to quantitative measurements that is often determined on retrospectively analyzed samples. The cut-off is an inherent part of qualitative IVDs and should be available before Phase III trials, for example, based on samples prospectively collected in well-designed Phase II trials. Sample size may be a critical issue, with an unreliable cut-off if too few samples are used; formulae are available in order to optimize the precision of the cut-off value and, hence, the clinical sensitivity and/or specificity of the test.

Two of the most important analytical performance characteristics to be validated are the test’s precision and accuracy. Precision indicates the closeness of agreement between replicate measurements under specified testing conditions. Such conditions determine the type of precision evaluated, ranging from repeatability to reproducibility. For qualitative tests as companion diagnostics, the closeness of agreement is evaluated against the majority call for a given sample. For qualitative tests, analytical accuracy refers to a pair of agreement measures, positive and negative percent agreement (PPA, NPA), with a reference standard. In analytical validation, it is essential to assess agreements between a candidate CDx and a reference standard. When a single measurement of the test under validation and the reference are available in the validation study, it becomes impossible to disentangle bias from random error, as well as accuracy from precision.

With regard to clinical validation, the ideal pathway for co-development of the drug and its CDx has been outlined by FDA as in Figure 1 below, which displays the parallel activities that should ideally take place for the drug and the biomarker.

Therefore, clinical validation spans Phase II and III trials, the latter including both pivotal and confirmatory trials, when needed. Moreover, in the ideal scenario, pivotal and confirmatory studies will be used to assess the clinical utility of the drug and the CDx simultaneously. Therefore, both in Phase II and III clinical trials, biomarker-driven trial designs assume fundamental importance in the era of precision medicine.

There are several clinical-trial designs which can be useful in the co-development of the drug-CDx pair.

 The choice among these designs depends on several issues, such as the clinical development phase, the degree of validation of the biomarker, and the need to assess both biomarker-positive and biomarker-negative patients. Enrichment designs, for example, will exclude biomarker-negative patients, and will often randomize biomarker-positve patients to the experimental drug or control. There are numerous examples in oncology of designs of this type; one recent case is the Phase III trial of osimertinib in the first-line therapy of advanced NSCLC with an EGFR mutation.

Another design that only includes biomarker-positive patients is the basket trial, which is often used in Phase II and allows enrollment of different cancer types harbouring the same molecular alteration. In this case, all patients receive the experimental drug, but nothing prevents researchers to also randomize their patients when this is considered feasible. With regard to the trial mechanics and statistical underpinnings, at least four types of basket trials have been proposed:

Exploratory designs, not powered, which may be used in one or more cohort of patients, defined, for example, on the basis of tumor types.

Classical Simon’s two-stage design, which may be used in one or more cohort of patients, defined, for example, on the basis of tumor types.

Bayesian basket design, which allows statistically formal borrowing of information across tumor types.

Sargent’s design, which allows informal borrowing across tumor types.

As a recent example of a biomarker-driven clinical trial with informal borrowing across different tumors, we were faced with the development of a novel drug for patients with one of five tumor types (NSCLC, melanoma, renal-cell cancer, triple-negative breast cancer, and castration-resistant prostate cancer), all unmet medical needs. For each of these tumors, monotherapy and combination were of interest to the sponsor. For safety and dose-finding, we proposed a randomized 1:1:1 design between low-dose monotherapy, high-dose monotherapy, and dose-escalating combination.

Once the best dose for monotherapy and combination were known, we implemented a randomized stratified Phase II design for each indication, allocating patients to the single-agent arm or the experimentally tested combination therapy.

This resulted in 10 individual single-arm trials, two for each of the five tumor types, and one each for monotherapy or combination. In each trial, the design allowed for two interim analysis, the first using Gehan’s rule, and the second consisting in a Sargent’s two-stage design (see Figure 2 below).

Unlike conventional Phase II designs, which allow for a “positive” and a “negative” outcome based on observed responses, Sargent’s design allows for a third, “inconclusive” outcome, in which the response rate is neither so low as to stop development or so high as to warrant a Phase III trial. When the outcome is inconclusive, the sponsor can decide to continue or stop the development based on other considerations, including safety and informal borrowing of information across strata. One potential advantage of this design is the typically smaller sample size, when compared with conventional Phase II designs.

Nevertheless, the trial consisting of 10 individual single-arm designs still has a considerably large sample size, with a maximal enrollment of 480 patients. This maximum sample size would only be reached if for all trials both futility bars are successfully passed. Interestingly, this sample size is driven by the analytical performance of the test, since the observed treatment effect will be diluted for a biomarker with poor diagnostic accuracy. In a biomarker-enrichment study, the dilution factor implicitly applied to the true treatment effect depends on the tests PPV and “R”, the ratio of treatment effects in true biomarker-positive over biomarker-negative patients.

More specifically, this dilution factor is (1-PPV) x R, and this relationship is depicted in Figure 3 below.

 Even for biomarkers with a reasonably high accuracy of 90% and relatively low ratio of effects in biomarker-positive vs. -negative patients of 2, the dilution effect will be already 10%. With a more modest treatment effect, a higher sample size is needed to significantly show the experimental drug or regimen reaches better clinical outcomes compared with the current standard of care.

A popular strategy for co-development entails the implementation of a bridging study, applied when the pivotal clinical trial was conducted with another assay than the CDx under validation. A bridging study consists in assessing the concordance between the clinical-trial assay (CTA) and a new assay that is intended to be a CDx. According to the FDA, the problem to be addressed in bridging studies is to estimate the drug efficacy in the CDx-defined subpopulation; in other words, to confirm that the clinical benefit of the drug would have been maintained had the CDx IVD kit been used instead of the CTA. The statistical approach in this case depends on the availability of samples from the pivotal trial, as well as the design of such trial (e.g., all-comers vs enrichment designs). When no or insufficient samples from the pivotal trial are available, an external concordance study should be considered.

This is also the case for the validation of a follow-on CDx. A follow-on CDx is an 

 companion diagnostic device that seeks the same therapeutic indication in its intended use as in the intended use of a the approved CDx.

 In this case, the design and estimation of performance depend on the availability of a reference test and on the sampling distribution of results both for the follow-on CDx and the CDx.

Our experience suggests that analytical performance drives clinical performance. A flawed analytical and/or clinically validation can jeopardize a biomarker’s and drug’s clinical utility. Therefore, statistical rigor is needed throughout the development and validation processes of biomarkers.

FDA-NIH Biomarker Working Group. BEST (Biomarkers, Endpoints, and other Tools) Resource [Internet]. Silver Spring (MD): Food and Drug Administration (US); 2016. Co-published by National Institutes of Health (US), Bethesda (MD).

Mok TS, Wu YL, Thongprasert S, et al. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. 

Food and Drug Administration. In Vitro Companion Diagnostic Devices Guidance for Industry and Food and Drug Administration Staff. Available at 

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http://www.asq509.org/ht/a/GetDocumentAction/i/121784

Freidlin B, McShane LM, Korn EL. Randomized clinical trials with biomarkers: design issues.

Buyse M, Michiels S, Sargent DJ, et al. Integrating biomarkers in clinical trials. 

Ramalingam SS, Vansteenkiste J, Planchard D, et al. Overall Survival with Osimertinib in Untreated, EGFR-Mutated Advanced NSCLC. 

Simon R. Optimal two-stage designs for phase II clinical trials. 

Simon R, Geyer S, Subramanian J, Roychowdhury S. The Bayesian basket design for genomic variant-driven phase II trials. 

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Li M. Statistical Methods for Clinical validation of follow-on companion diagnostic devices via an external concordance study. 

PhD, is Director of Consulting Services, 

Articles

Recent case study highlights the importance of applying statistical rigor throughout the development and validation processes of biomarkers.

Integration of Biomarker Validation in Oncology Trials

Immunotherapy has revolutionized cancer treatment strategies for a variety of hematological and solid tumor malignancies. Two main therapeutic approaches, chimeric antigen receptor T-cell therapies (CAR-T) and checkpoint inhibitors (CPI), have emerged as promising immunotherapies and have been successful at improving patient prognosis. While the development of next-generation CAR-T and CPI strategies continues to expand upon an already diverse immunotherapy landscape, there are significant differences that can influence the conduct of early-stage clinical trials using these approaches.

CAR-T therapy is a type of immunotherapy that genetically modifies a patient’s own T-cells to recognize and destroy cancer cells. While there are many clinical trials underway for a variety of tumor types, CAR-T therapy has emerged as a promising strategy for the treatment of blood cancers. In comparison, CPI therapeutics work by blocking checkpoint proteins on T-cells or tumor cells from binding with partner proteins, that enhances T-cell killing of cancer cells. CPI drugs have been approved in a variety of cancer types.

Both immunotherapies are currently being used in early-stage clinical trials for cancer research. However, a simple way to describe the comparison between CAR-T and CPI is “process versus product.” The investigational drug in a CAR-T trial is the end product from a manufacturing process in which T-cells are collected from patients via apheresis, then genetically engineered to express chimeric antigen receptors on their surface. The modified T-cells are expanded to significant quantities, frozen, then infused back into the patient; this process is similar to a blood transfusion. Patients need to be hospitalized for the infusion and will remain hospitalized for a few days or weeks dependent on their condition as well as the risk of side effects. In comparison, CPI drugs are most commonly a monoclonal antibody product that is typically administered by an IV infusion over several hours to patients in the outpatient setting. While both immunotherapeutic approaches have yielded successful results for patients, there are risks and challenges of each that should be considered.

CAR-T has shown tremendous success in adult and pediatric patients. Novartis made headline news with the launch of Kymriah in 2017 as a one-time treatment for B-cell acute lymphoblastic leukemia (ALL), showing a remission rate of greater than 80% after three months in patients who do not respond to standard of care treatments. A second CAR-T cell therapy, Yescarta, was approved for patients with large-B-cell lymphomas whose cancer has progressed after receiving at least two prior treatment regimens.

More recently, in late July, CAR-T drug Tecartus was approved by FDA for the treatment of mantle cell lymphoma in patients who have not responded to other treatment types or relapsed following treatment.

The CAR-T therapy landscape has been most effective on blood cancers, but what progress has been made on solid tumors?

Many strategies have emerged to improve the efficacy of CAR-T therapies for solid tumors, however, several challenges have been identified in recent years. These include intricacies of solid tumors and their locations in the body, hostile tumor microenvironments, toxicities, and undesired antigen specificity. Alternative next-generation approaches for the treatment of solid tumors are currently in development.

One of the major challenges for use in CAR-T therapy is the inappropriate targeting of CARs that cause adverse events, including cytokine release syndrome and the increased incidence of neurologic events. Most of the CAR-T cell target antigens seem not to be tumor-specific and shared by normal cells. Therefore, antigen specificity becomes a crucial factor for CAR-T therapy.

As with CAR-T therapies, CPIs have also proven efficacious, while also bearing risks. There are a number of CPI drugs on the market that have shown anticancer activity against a variety of cancer types. Evidence of benefit has been reported when CPIs are combined with certain chemotherapies and radiation treatments, as well as other immunomodulatory drugs. CPIs have also shown to be effective in the adjuvant setting for some cancers. Major risks associated with CPI include a variety of immune-related adverse events, including graft-versus-host disease (GVHD) and widespread inflammation.

What does the immunomodulatory therapy pharma landscape look like?

Organizations working on immunomodulatory therapies include large pharmaceutical companies as well as emerging biotechnology companies with exciting new approaches for patients. There are also many startups and university spinouts focused on novel approaches to immunomodulation to treat cancer patients.

Highly innovative universities and research centers, such as the University of Pennsylvania and the City of Hope National Medical Center, not only provide new technologies for evaluation, but they also provide the infrastructure for the manufacture and testing of new immunotherapies for future commercial development.

What else should be considered when it comes to these clinical trials?

Consider using an oncology-focused CRO to support the improved and accelerated development of novel immunotherapies. It is critical that the CRO be familiar with the logistics for CAR-T and CPI trials that can vary by therapeutic type, patient population, and indication. Also, it is imperative that the medical monitors and the clinical team need to be familiar with the type of trial, indications, patient profiles, safety concerns, and operational logistics. For example, patients may experience unanticipated adverse events with each immunotherapy, meaning that it is critical that the clinical team be experienced and fully prepared throughout the study. Since having extensive management experience for complex clinical trials is key, a CRO’s strategic expertise can help keep clinical trials operational, while providing optimal patient safety and efficacy.

Distinguishing CAR-T and CPI approaches and the clinical trial challenges and complexities associated with each.

Immunomodulators and Cancer Research

 that interruptions of clinical trials due to COVID-19 have been on the decline since June, this 

, also from GlobalData, detailed the reasons behind trial disruption. The primary one, at 67.3%, was suspension of enrollment; delayed initiation of planned trials followed at 18.4%, and slow enrollment at 14.4%. Of the trials affected by the latter, 20.7% were due to the availability of sites and investigators.

The majority of disrupted trials were in Phase II, at 44.8%; Phase I, with 26.1%; Phase III, at 21.7%; and Phase IV, with 7.4%. By therapeutic area, oncology has the highest number of disrupted trials, with 33.3%, followed by CNS, at 16.1%, infectious disease (9.3%), gastrointestinal (9.1%), and respiratory (7.7%).

But, as the data showed, trials are coming back again. And that’s where the cracks in the traditional approach are being exposed. It is why so many articles and observations from experts in clinical trials were calling on the industry to adapt, learn, and change so the fundamental breakdowns in clinical trials can be addressed. You can peruse our online articles and blogs from the past four months for a clearer picture of the calls to action.

 we posted was from Gen Li, PhD, president and founder of clinical development analytical products and services provider Phesi. In this article, Li urges the industry to reexamine its delayed, suspended, or low-enrolling studies on a deeper level. Clearly, sites and investigators were unavailable during the early days of the pandemic in the Northeast and now again in the South. But what other factors existed besides COVID?

Li suggests that many trials are poorly designed from the outset, “so their execution is intrinsically flawed—and would be highly likely to fail or require rescue, even if COVID-19 had never happened.” Specifically, Li says that poorly executed site activation is one of the main drivers of slow patient enrollment. If sponsors now take a data-driven approach, by identifying high-performing sites or finding the most relevant CRO with a performance record in the indication under study, they could potentially avoid a trial destined for failure.

Another area of examination? Competition between studies and sites, which has significant impact on patient enrollment. Li uses the example of the number of recruiting sites in Crohn’s disease that increased in the three years before COVID-19, from under 2,000 to more than 9,000, and without acknowledgment of the limited patient population. This has led to poor country allocation and site selection. It leads to the reality that some of these programs will have to be terminated and reallocated to those with the best chance of succeeding.

Many have taken advantage of the processes and technologies to help overcome the limitations of trials compounded by the pandemic. We look forward to showcasing more success stories around these technologies as well as their acceptance by the global regulatory authorities to ensure trial continuation. But for long-term change, it will take a concerted effort by many to keep trials moving in an upward motion toward excellence.

While clinical trials are starting to make a return from COVID-19-related interruptions, cracks in their traditional operation are being exposed.

COVID Exposes the Cracks in Trial Problems

The Pediatric Research Equity Act (PREA) and the Best Pharmaceuticals for Children Act (BPCA), have driven pediatric research efforts resulting in over 800 medicines being labeled for use in children. PREA gives FDA authority to require pediatric assessments (either filed with the initial application or deferred) for the “claimed indication” for any application for a new active ingredient, new indication, new dosage form, new dosing regimen, or new route of administration, unless such assessments have been waived. When pediatric assessments (studies) are required, the sponsor must submit an initial pediatric study plan (iPSP) to FDA detailing its plan to fulfill its PREA requirements.

Unfortunately, PREA has failed to promote research for pediatric cancers. Most oncology products are developed for adult cancer indications that do not occur or rarely occur in children, making studies in children impossible or highly impracticable, resulting in studies being waived. Even if the rare adult cancer occurred in children, most will have orphan-drug designation and thus are exempt from PREA requirements.

The Research to Accelerate Cures and Equity (RACE) for Children Act, an amendment to PREA as part of the 2017 FDA Reauthorization Act, goes into effect on Aug. 18 and aims to change the landscape and promote pediatric cancer drug development.

This new Act requires sponsors to submit an iPSP with any original new drug application or biologics license application for an oncology product “intended for the treatment of adult cancers and directed at a molecular target substantially relevant to the growth or progression of a pediatric cancer.” This requirement applies even if the proposed cancer therapy has orphan-designated indications or is being developed for a cancer that only occurs in adults, if the molecular target (mode of action) is relevant to pediatrics.

The iPSP needs to include an outline of the planned pediatric investigation(s), any request for deferral or waiver with supporting documentation, and be submitted to FDA within 60 days of the end-of-Phase II meeting.

The RACE for Children Act is challenging because multiple indications may need to be investigated to address the entire pediatric population (i.e., children ages 0-2 years, 2-11 years, and adolescents ages 12-<17 years). There are significant differences between children and adults in disease physiology, pharmacokinetics (PK), and pharmacodynamics (PD), and they are especially evident in children under two years of age. As a result, different age groups may require different drug formulations and dosing.

Limited sample size, more complex PK sampling strategy, and lack of clinically meaningful and measurable endpoints are just a few of the pediatric issues that need to be addressed.

Furthermore, sponsors will likely need to plan their first study in children, define dose-finding and formulation strategies, and efficacy population and endpoints before they fully understand the drug’s activity in adults and have identified potential developmental toxicities.

Model-informed drug development (MIDD) can help address many of these challenges. Population PK models with adult data can be appropriately scaled to pediatrics, integrating maturation and disease factors using allometric scaling to determine the best dose for the first pediatric trial cohort. Physiologically-based pharmacokinetic (PBPK) modeling and simulation can also be used to model drug performance and assess drug-drug interactions in neonates and onwards.

Preparation is important for optimally managing this new regulatory requirement.

Review FDA guidance on implementing studies of molecularly targeted oncology drugs, the content and process for submitting an iPSP4, the Relevant Molecular Target list, and the Non-relevant Molecular Target list. While these target lists provide useful direction, they are not binding. Anticipate it taking 210 days to progress from iPSP FDA submission to either agreement or receipt of a non-agreed letter.

Ask for advice regarding iPSP development from the Oncology Center of Excellence Pediatric Oncology Program and the Oncology Subcommittee of the Pediatric Review Committee.

Consider requesting formal and parallel scientific advice from FDA and the European Medicines Agency (EMA) to avoid unnecessary duplication of pediatric studies.

Leverage real-world data and knowledge from the literature and adult studies to bridge the data gap for pediatric patient populations. In certain cases, it is permissible to enroll adolescents with adults in Phase III trials and obtain early pediatric data. FDA issued draft guidance in 2019 allowing this if sponsors have obtained PK and toxicity data and the adolescent patients have recurrent cancers or no other treatment option.

Use MIDD—which has been adopted by FDA and EMA—to support dose optimization, provide evidence of efficacy, and improve clinical trial designs. MIDD can also help reduce the size of trials or eliminate the need for trials in some circumstances.

Pediatric patients deserve safe and effective therapies that have been evaluated for their stage of development. MIDD can help sponsors to meet the RACE for Children Act’s endeavors to facilitate inclusion of more pediatric dosing information on new drug labels.

, RN, MSHS, RAC, is Vice President, Regulatory Strategy, at 

An amendment to Pediatric Research Equity Act, as part of the 2017 FDA Reauthorization Act, goes into effect soon aiming to change the landscape and promote pediatric cancer drug development.

The RACE for Children Act Takes Effect This Month

Personalized medicine has been a rapidly growing field in the healthcare sector, but what does that mean for clinical trials? Since this therapy is typically specific to one person, the processes need to be handled carefully, and personnel need to be highly trained and diligent to ensure that the correct therapy is going to the right patient. However, this is just one aspect of the careful coordination required for a clinical trial with personalized medicine.

Adaptimmune is currently developing and investigating a type of personalized medicine known as T-cell therapy in multiple clinical trials. This type of cell therapy leverages an individual’s own immune system to fight cancer. The company engineers T-cell receptors to target solid tumors, which are inserted into a patient’s own T-cells to arm them to identify and kill cancer.

The autologous cell therapies developed by Adaptimmune, called SPEAR (specific peptide enhanced affinity receptor) T-cells, start with the collection of leukocytes (white blood cells) from patients who are undergoing treatment for various cancers. The cells are collected in a clinical setting via a process called apheresis and then shipped to a centralized manufacturing site. The T-cells are then isolated from the apheresis collection starting material, genetically modified with the SPEAR T‑cell platform, and expanded in cell culture to produce SPEAR T-cells.

Adaptimmune is committed to providing safe and effective cell therapies to patients. The company tests every SPEAR T-cell therapy rigorously to meet specifications for identity, sterility, potency, and dose. These SPEAR T-cells, with enhanced functionality to recognize and attack solid tumors, are then infused back into the patient.

The development lifecycle of SPEAR T-cell therapies shares many common features with that of biologics and other complex pharmaceuticals. Autologous T-cell therapies have some unique challenges and opportunities during clinical development, though. In early-stage development, all first-in-human studies focus on establishing safety and defining an effective dose. T-cell therapies add a new twist to early-phase trials because the engineered T-cells can rapidly expand after infusion and persist in the patient’s immune system, enabling the engineered T-cells to persist for years.

In early-stage clinical trials with T-cell therapies, dose escalation designs are often employed that balance risk of unknown adverse events with the possibility of achieving anti-tumor efficacy. Each patient provides a new window into critical quality attributes of the product that correlate with T-cell engraftment, persistence, and anti-tumor effects. Very few therapeutic approaches have evolved as rapidly as autologous T-cell therapies, because a new product lot is manufactured for each patient. As the product profile becomes better defined, the manufacturing and treatment protocols can be changed and adjusted to improve efficiency. To account for this continuous improvement, it is common for investigational new drug (IND) applications of cell therapies to have many more amendments than other more traditional products. The opportunities for rapid learning, and rapid product improvement, are unique to this personalized approach.

As Adaptimmune moves T-cell therapies into late-stage testing, the manufactured product becomes tuned for efficacy, innovation focuses on scaling the supply and distribution to large populations, and the company works to optimize the patient journey to integrate with these therapies unique product manufacturing. Adaptimmune is constantly looking to improve SPEAR T-cell therapies in both early- and late-stages of product development.

In early-stage development, the company is looking to improve its therapies in a number of ways, including:

Manufacturing engineered T-cells specific for cancer targets using a patient’s own T-cells.

 Adaptimmune genetically modifies each patient’s T-cells with a highly engineered T-cell receptor that optimally engages a tumor antigen and is intended to ensure product potency and safety.

Minimizing variability between product lots. 

The apheresis starting material for T-cell therapies is highly variable between patients. Diversity in T-cells with the apheresis reflects inherent patient genetic variability, different immune system challenges during the patient’s life, and receipt of different lymphotoxic cancer therapies prior to enrolment in a T-cell therapy protocol. T-cell selection from apheresis starting material for manufacturing and sophisticated in-process testing help to minimize the impact of variability in the apheresis material.

Optimizing an efficient manufacturing process.

 Use of automation, electronic data capture, and closed manufacturing systems are being tested and implemented to make the current good manufacturing practice (cGMP) activities faster, more reliable, and less labor intensive.

Employing state-of-the-art analytic capabilities.

 Optimized analytics enable rapid product characterization. Identification of critical quality attributes of T-cell products is used to tweak key process parameters.

Correlating product attributes with clinical outcomes.

 Cytokine levels in patient serum, dynamics of T-cell persistence after transfer, and single-cell T-cell analysis of phenotype and function for persistent cells are routinely measured. Gene expression patterns, cell surface expression of proteins, and trafficking attributes of T-cell populations are evaluated to identify correlates of effective anti-tumor therapy.

Identifying new approaches for treating solid tumors. 

Deep understanding of the mechanism of T-cell efficacy and the attributes of potent T-cell products can be translated into better products, and then investigated in small cohort clinical trials, which are focused on obtaining efficacy and safety data quickly.

Investigating next-generation T-cell products, such as those with multiple genes.

 In addition to the SPEAR T-cell receptor alpha and beta genes, the CD8alpha co-receptor gene can be introduced to autologous T-cell products. For example, ADP-A2M4CD8 is being used in the SURPASS trial to engage the patient’s CD4+ T-cell compartment, which is intended to enhance therapeutic potential.

 The impact of combined immunotherapy will be evaluated. Adaptimmune will initiate a Phase II trial combining ADP-A2M4 with pembrolizumab (SPEARHEAD-2) in patients with advanced head and neck squamous cell carcinoma. This will be the first time a SPEAR T-cell drug is used in sequence with first-line systemic therapy, namely ADP-A2M4 SPEAR T-cells and a PD-1 inhibitor. Adaptimmune has reported data showing that PD-L1 upregulation in response to SPEAR T-cell tumor infiltration and activity may represent a mechanism of resistance (SITC 2019).

As the company’s products enter late-phase clinical trials, including registration trials for filing biological license applications (BLAs), other types of innovations are being explored, with some aimed at generating manufacturing and delivery systems for scalable global supply. Two areas of focus for Adaptimmune are: ensuring a robust chain of custody and chain of identity and optimizing cold-chain logistics.

A key priority for Adaptimmune is the patient experience, including minimizing the time between identifying an eligible patient and delivering their autologous cell therapy for infusion. Opportunities for new technologies for improved speed and reliability are seen in logistics and supply chain, managing lymphocyte collection at apheresis sites, scheduling manufacturing slots at the centralized manufacturing facility, and ensuring capacity at treating hospital centers.

Adaptimmune has partnered with Vineti, a provider of supply chain software with a personalized therapy management (PTM) platform. Investment in bespoke software solutions for unique challenges with patient scheduling, product tracking, and patient sample management ensures scalability, while maintaining the standards of quality and regulatory compliance. Similarly, Adaptimmune is investing in development of manufacturing execution systems and enterprise resource planning software to ensure optimization of production as the company moves closer toward a commercial product.

Decreasing the time for manufacturing and simplifying the release testing is very important to improving the patient experience. Additional innovation will allow patients and physicians to engage with the production of the autologous therapy and follow the “cell journey” during the transformation from apheresis product to final product. Similarly, an opportunity exists to explore performing patient therapy steps outside of traditional clinical centers to bring autologous T-cell therapies closer to patients. While there are many advantages to a centralized manufacturing model, and to a high-volume clinical treatment facility, there are also opportunities to bring apheresis and follow-up services closer to the patient’s home. The COVID-19 pandemic has magnified the impact and value of such distributed approaches for many aspects of healthcare delivery. Adaptimmune is evaluating approaches that simplify the patient experience, decrease risks of travel, and increase visibility for physicians and patients.

In early-stage development, flexibility is a key factor and “speed to success” strategies allow exploration of many approaches to get to the best product. Adaptimmune’s decision to build a fully integrated cell therapy company, with a range of in-house capabilities, enables it to identify innovations and adjust processes quickly. The company’s in-house manufacturing capabilities allow it to transition from an exploratory development stage to one focused on supply and distribution—ultimately leading to more effective products that can be delivered more efficiently to patients with cancer.

Success in cell therapies targeting solid tumors will progress rapidly as the field gains experience. Many solid tumors remain difficult to treat, thus requiring new and improved approaches. Adaptimmune is applying what it learns via translational sciences to better understand the attributes of individual cancers and their interaction with the immune system. As a result, T-cell therapies can be targeted appropriately, and persist in patients, while overcoming tumor microenvironment and resistance mechanisms that are unique to each cancer. Developing these therapies with constant reference to the patient and physician experience is key.

The future of cell therapies in the clinic

Autologous therapies have the potential to change cancer treatment as we know it. Adaptimmune has been working in autologous cell therapies over the past decade, and the positive results it has seen in clinical trials have been encouraging. The company initiated a Phase II trial, SPEARHEAD-1, in synovial sarcoma and myxoid/round cell liposarcoma, which it believes could be used for registration as the company aims to make its first therapy available in the U.S. in 2022. In addition, this year at the 2020 American Society of Clinical Oncology (ASCO) Annual Meeting, Adaptimmune reported responses in multiple solid tumor types, including sarcoma, esophagogastric junction (EJG), head and neck, and lung cancers with its first-generation ADP-A2M4 SPEAR T-cells and next-generation therapy ADP-A2M4CD8 SPEAR T-cells. Based on early promising data in EJG cancer, Adaptimmune plans to start another Phase II trial next year with ADP-A2M4CD8.

These therapies can be given to any patient and do not depend on making modified cell products from each individual patient’s cells. This type of platform derives universally acceptable immune cells from stem cells and could completely change the patient experience by delivering “off-the shelf” cell therapies.

Adaptimmune has been developing an allogeneic platform and recently presented findings at the 2020 American Society of Gene &Cell Therapy (ASGCT) Annual Meeting. Data presented summarized recent advances in Adaptimmune’s allogeneic platform, demonstrating the production of engineered T-cells, differentiated from human induced pluripotent stem cells (hiPSC) (iT cells). These findings suggest that, like autologous SPEAR T-cells currently in clinical trials, Adaptimmune’s ADP-A2M4 iT-cells have the potential to be an efficacious cell therapy.

Allogeneic products are often referred to as “on-demand” or “off-the-shelf,” in contrast to autologous products that are manufactured 

 for each patient. The possibility of manufacturing in advance of demand allows storage and stocking of the therapeutic agent. Eventually, this could mean that these products could be used in community hospitals instead of restricting treatment to larger academic centers, as is the case with autologous cell therapy now. The time it takes to access treatment is critically important to people with cancer at all stages of diagnosis—making fast delivery of treatment a key priority for all cell therapies.

Adaptimmune is committed to building on its preclinical testing expertise and the clinical success of its autologous therapies to direct the evolution of its stem cell-derived allogeneic platform. Both autologous and allogeneic cell therapies are important in the fight against cancer. Working on both platforms simultaneously allows the translational learnings from autologous SPEAR T-cell clinical trials to be applied to the development of new SPEAR T-cell products and new platforms such as allogeneic—with the aim to speed the generation of more accessible treatments for people with cancer.

A look at one company’s platform approach in enabling the engineering of T-cells to identify and destroy cancer.

Designing Cell Therapies to Target Solid Tumors

Issue PDF

Click here for a link to open the Applied Clinical Trials August 2020 issue in an interactive PDF format.

Applied Clinical Trials, August 2020 Issue (PDF)

Cell therapy clinical trials typically generate significant quantity and diversity of biologic data intended to characterize disease and patient biology, as well as data intended to demonstrate evidence of therapeutic mechanisms. With the rise of precision medicine, similar expansions of data generation are occurring across therapeutic areas—though cell therapy particularly emphasize the critical role of molecular biomarkers for early identification of risk factors for adverse events and to measure the durability of therapeutic mechanisms.

These biologic data are rich resources that can both inform the ongoing clinical program and further represent an opportunity for organizations pursuing cell therapies to build data assets that create optionality at the program and portfolio levels. However, systems and processes for aggregating and integrating data within clinical programs have not kept pace with sponsors’ ability to produce biomarker data. Just as electronic data capture (EDC) technology revolutionized industry’s approach to clinical data management, we now see an imperative for strategic management of biomarker data.

In this article, we will explore the increasingly critical functions of capturing and integrating molecular biomarker data concurrent with ongoing clinical trials and establishing foundations for program and enterprise level data assets. Key elements align with findable, accessible, interoperable, and reusable (FAIR) principles and include:

A multilayered and unified approach to data processing that centralizes and aligns all key information across data sources.

Analytic and visualization capabilities that empower stakeholders with skill sets covering clinical, biologic, and data sciences.

Strategic implementation to support current or potential future efforts to integrate additional external data and information—including from publicly available data sources.

Successfully completing this shift from disjointed data to data asset can lead to massive scientific value creation.

Big data at the heart of precision medicine

Data generation in clinical trials has expanded exponentially as the cost of using complex assays to interrogate biological pathways has decreased, and sponsors continue to invest considerable time and resources to understand and implement cutting-edge modalities. These data, and data in the public domain, have a broad range of applications, from addressing patient selection, characterizing mechanism of action, to guiding dosing and optimizing study design. This is certainly evident in the discovery and development of cell therapies, for which molecular biomarkers characterize targets, can provide evidence of therapeutic durability, and have a critical role in identifying risk factors for adverse events. Unfortunately, these data are collected and generated from a myriad of sources and typically remain disconnected due to their complexity and disparate nature.

Today, these disjointed data have led to a resource-intensive approach to analysis, consisting of ad hoc efforts to compile the data needed to test a particular hypothesis or answer a specific scientific question, e.g., confirming therapeutic engagement with an intended target. Oft-cited studies show that organizations report spending >80% of time collecting/organizing data, at a significant detriment to capacity for analysis (not to mention that scientific teams report that data cleaning is the least enjoyable data science task).

 This potential impact can be especially stifling given that the depth and diversity of the data are generally intended as a powerful tool to inform on-trial decisions as well as ongoing development strategy.

This is especially true as an ever-growing set of biomarker assays are available, ranging from targeted genomic panels to high-content or high-throughput experiments. Data are now being generated at unprecedented rates from flow cytometry, next-generation sequencing, immunophenotyping, mutational analysis, gene or protein expression, and more. The diversity and complexity of biomarker assays is further complicated by the fact that the resulting data are generated in different formats and structures, creating challenges around harmonization, interpretation, and accessibility. Moreover, specialized labs and associated technologies have emerged and many have developed proprietary technologies, methods, or panels.

Scientific advancement is inherently unpredictable and delivering on the promises of precision medicine requires the ability for sponsor teams to flexibly interrogate and analyze data. In order to optimize value creation from generated data, drug developers and innovators need the ability to perform rapid data interrogation within and across platforms, trials, and geographies.

As with any big data opportunity, one key to success lies in developing a systematic approach to harmonizing the data. Our experience has shown that investment in comprehensive data alignment contributes exponential value downstream by enabling rapid and flexible analyses across the entirety of data sets, rather than spurring ad hoc efforts (each requiring incremental data alignment efforts) that yield ongoing delays that can stifle momentum—or miss opportunities to inform time-sensitive decisions with data that should already be available.

A multilayered and unified approach to data processing is critical to fully leverage the information and content produced across studies and experiments for scientific insight generation. To handle the complexity and throughput of biomarker assays and make data available to inform decision-making, best-practice approaches leverage:

Automated pipelines for the ingestion of data from diverse labs and biomarker assay technologies.

Assay-specific workflows and quality control parameters, as well as a capability to incorporate custom workflows.

Data reconciliation capabilities to expedite historically time-consuming reconciliation activities between laboratory information management systems (LIMS) and EDC.

A centralized database for storage and access to all specialty lab data post-ingestion with the ability to support production of submission-ready data sets that comply with Clinical Data Interchange Standards Consortium (CDISC) standards and can be adapted to shifts in regulatory requirements.

The increasing availability of public data sets, such as The Cancer Genome Atlas (TCGA) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI), offer a transformational opportunity for insight-driven planning at all phases of the development lifecycle. These public data sets are often of considerable size for life sciences data, compiling billions of data points across multiple modalities and representing data that would have previously required many years and millions of dollars to generate. Many organizations now recognize the opportunity to integrate publicly available data with their proprietary data assets to immediately adopt more rational approaches to trial design, patient stratification, and portfolio strategy.

We see progressive organizations taking a strategic approach to compiling and integrating publicly available data from their own preclinical and clinical programs to exponentially increase their capability to develop and test hypotheses quickly and fuel a more data-driven approach to clinical planning.

Precision medicine development is a truly multidisciplinary endeavor, combining deep biological, scientific, clinical development, regulatory, and further stakeholders. Organizations that are able to provide access to organized data sets and facilitate collaboration across these groups have a material advantage in realizing the full potential of these teams, particularly those collaborating on active development programs.

The opportunity for effective collaboration is extended given the prevalence of partnerships and licensing relationships as strategies to support the development of novel therapeutics. The ability to gather data and insights to demonstrate early signs of positive biological response in early-phase trials can further support increasing partnerships, licensing, and fundraising activities.

User-friendly, intuitive web-based tools designed for biomarker analysis and data visualization are a particularly valuable opportunity to facilitate these collaborative efforts. Such platforms have the benefit of expanding access to data exploration to biologists, translational scientists, and other teams for which data science and coding experience may be capacity-constrained resources. However, such tools are unlikely to fully satisfy the requirements of all stakeholders, as data scientists within a bioinformatics team will ultimately require direct access to raw data to enable thorough and more formalized analysis and exploration.

Strategies to comprehensively integrate biomarker data must support the needs of these diverse stakeholders, providing intuitive visualization and analysis capabilities designed to support biomarker exploration while also delivering direct access to raw and processed data, visibility into quality control and processing pipelines, and interoperability with software tools leveraged by both translational and informatics groups (e.g., custom R packages, GraphPad Prism, Spotfire).

Given the investment in generating molecular biomarker data and its potential to radically increase an organization’s capability to advance the understanding of diseases, discover new drug targets, and/or identify biomarkers, we are quickly moving toward an era where proactive and continuous data analysis is the expectation. Moreover, we cannot simply take comfort in the promise of multiyear efforts aligned with timely buzzwords from “Big Data” to “Data Lakes” and “Machine Learning.”

Delivering on the promise of precision medicine requires out-of-the-box thinking and platforms designed to efficiently unlock the full potential of the data generated. Most important, we believe this must prioritize both the potential to advance ongoing clinical programs while setting the foundation for future enterprise systems.Just as EDC technology helped revolutionize clinical data management, technology-based solutions for biomarker data management will now become a requirement for modern clinical trial operations.

We must also recognize that technology alone is not enough. Ultimately, success requires a cross-functional team including biologists, clinical developers, translational scientists, and innovative data scientists with the skill to design, validate, and operate technologies engineered specifically to address the challenges of biomarker data management in the new paradigm of biomarker guided drug development.

Press G. “Cleaning Big Data: Most Time-Consuming, Least Enjoyable Data Science Task, Survey Says.” 

https://www.forbes.com/sites/gilpress/2016/03/23/data-preparation-most-time-consuming-least-enjoyable-data-science-task-survey-says/#278755f86f63

Exploring the benefits of capturing and integrating molecular biomarker data within clinical trials to build foundations for data assets.

The Importance of Biomarker Management

It is not often that regulation of clinical trials is eased. Usually the tendency is for rules to be tightened up—but necessity has proved the mother of invention in the case of clinical trials for products to combat COVID-19. The European Parliament rushed through an exemption from the onerous European Union requirement for prior environmental risk assessment in the case of products making use of genetically modified organisms—which, with the multiple current approaches using attenuated viruses or live vectors, is a scenario increasingly likely in vaccine development.

The exemption will permit clinical trials to start before the requirements of directives dating back as far as 2001 have been met. This legislation, notorious among sponsors of clinical trials, obliges sponsors to obtain written consent in advance from each of the member states where a trial is planned, on the basis of a case-by-case review of an environmental risk assessment. As the parliament resolution drily remarks, “experience shows that, in clinical trials with investigational medicinal products containing or consisting of genetically modified organisms (GMOs), the procedure to achieve compliance with the requirements of Directives 2001/18/EC and 2009/41/EC as regards the environmental risk assessment and consent by the competent authority of a member state is complex and can take a significant amount of time.”

Worse still are the impediments to multi-center trials. “The complexity increases greatly,” states the resolution, with multiple requests for authorization to multiple competent authorities in different member states in parallel—and with national requirements and procedures that “vary greatly from one member state to another.” Some countries require a single request for authorization to a single competent authority, but in others parallel requests need to be submitted to different authorities.

As if that were not challenging enough, “some member states apply Directive 2001/18/EC, others apply Directive 2009/41/EC, and there are member states that apply either Directive 2009/41/EC or 2001/18/EC depending on the specific circumstances of a clinical trial.” And other member states apply both directives simultaneously to different operations within the same clinical trial. There are also variations between national requirements as to the content of the technical dossier.

In consequence, “it is not possible to determine a priori the national procedure that is to be followed,” the resolution says. Attempts to streamline the process through informal coordination between member states’ competent authorities have been unsuccessful, and “it is therefore particularly difficult to conduct multi-center clinical trials with investigational medicinal products that contain or consist of GMOs involving several member states.”

Since the pandemic has created an unprecedented public health emergency and claimed the lives of thousands, as well as inflicting major disruptions to national economies and the EU, the plan is to ease that requirement so that remedies can be developed and be made available as soon as possible, the parliament reasons. And so that trials are not delayed “due to the complexity of differing national procedures put in place by member states,” it is necessary to grant a temporary derogation from the requirements concerning a prior environmental risk assessment and consent. This will last for the duration of the pandemic—or as long as COVID-19 is a public health emergency.

However, sites where the genetic modification of wild-type viruses and related activities take place will still be required to comply withthe legislation, so the manufacturing of medicinal products containing or consisting of GMOs intended to treat or prevent COVID-19, including investigational medicinal products, will be excluded from the temporary derogation.

Sponsors will also be required to minimize negative environmental impacts. And the environmental impact of exempt products “will continue to be assessed by the EMA in parallel with the evaluation of the quality, safety, and efficacy.” Compliance with ethical requirements and good clinical practice in the conduct of clinical trials continues to be mandatory as well as compliance with good manufacturing practice in the manufacture or importation of investigational medicinal products containing or consisting of GMOs.

 is a freelance journalist who specializes in European health affairs and is based in Brussels, Belgium

Amid the COVID-19 pandemic, the EU is allowing trials to start before the requirements of directives dating back as far as 2001 have been met.

Clinical Trials Can Duck the European GMO Problem       

The COVID-19 crisis is not going to last forever, but its impact on clinical trials may. Future clinical trials that have the best chance to proceed may be those that decentralize and effectively engage with patients. In this interview, Michael Woods, CEO of Firma Clinical Research, shares why COVID-19 may force greater efficiency for trial designs and greater access for trial participants.

Moe Alsumidaie: What does the future of successful clinical trials look like?

 I believe COVID-19 challenges will force the industry to design trials with greater efficiency and greater access for trial participants. That will involve a variety of patient-centric solutions to enhance recruitment, retention, and the entire trial experience for the participants, including home health visits and technology, to support more remote access. A significant change will be listening to the patient’s needs with greater focus.

Trials that adopt decentralized and patient-centric approaches will simply be more competitive in attracting research participants. I believe the patient-centric changes will happen quickly, as will the more rapid collection of data to support the development of a drug or device. Those who fail to adapt will suffer a competitive disadvantage.

MA: After COVID-19, fewer patients are willing to go to study sites. How do patient-centric approaches help to recruit and retain these participants?

 Home-health visits can lower risk and make it easier for a research subject to participate because there’s no negotiating going into a doctor’s office, clinic, or hospital, where the perceived risk is often far higher. A home-health visit occurs with personal protective equipment, and social distancing to minimize the risk of potential COVID transmission. A nurse or phlebotomist communicates in advance with each research participant to ensure visit expectations are understood and to gain the risk perspective of the participant. When you have participants at higher risk—the elderly, pediatrics, rare disease populations—there is an ease and safety advantage to have the research come to them.

MA: What types of studies are most appropriate for at-home health services?

 Home health services are appropriate for participants with compromised mobility or underlying conditions. Rare disease populations often live far from research sites, so easing the travel burden for those populations is a huge advantage. And if there are conditions that are somewhat caregiver intense, it’s much easier for the research participant to be seen in the home rather than having the caregiver coordinate transport to a clinic or hospital.


MA: How can sponsors expand access to research by employing home-health services?

 There’s no question that home-health services can extend the reach of a site by hundreds of miles and save the participants a great deal of travel. One of the biggest challenges that we hear from sites is that subjects don’t want to travel or express concerns that the subject stipend they receive is not enough to cover travel expenses. By deploying home-health nursing, sponsors can not only expand a site’s reach to remote locations but also retain these patients. The key to operationalizing this is to deploy and train home-health nurses who are local to the research participant.

MA: Tell me about the more complex procedures that need to be conducted at home.

 That comes down to the amount of training available to home-visit nurses and what is required to support a specific procedure or collection of a data point. If it involves equipment that is easily transported into a home, like an infusion pump or a centrifuge for spinning down blood, that lends itself to home visits. Mental health assessments and scales that are used for behavioral analysis can be administered by home health if the nurse is trained to apply those tools. You also can combine the nurse visit with telemedicine. A physician or other study staff member can conduct assessments virtually, with the nurse in the home also simultaneously collecting data.

I believe we will see an increasing number of procedures being conducted in the home, as equipment that supports those procedures improves and becomes more mobile. Also, as telemedicine technology is growing and it becomes more widely used, I think you will see more dedicated research resources in the home setting. This mirrors what I expect to see in healthcare in general.

MA: What clinical trial training requirements do home-health nurses have to undergo?

 All nurses should be experienced in administering healthcare procedures in the home. A typical home visit to support research includes the collection of blood, body fluids, or other biological samples, a general or specific physical examination, and the collection of vital signs. Additionally, nurses should be trained on protocol-specific procedures, including sensitivity to the research subject’s condition, such as mobility or mental state. Training should also include GCP, and all training documentation must meet the satisfaction of the overseeing investigator, CRO, or sponsor.


MA: How could sponsors differentiate between a general home-health nursing service vs. a clinical trial-specific home-health nursing service?

 Sponsors should look for home-health services that focus on the relationship between healthcare professionals and the research subjects. It involves strong communication to manage that visit and the human interaction and to make it a relaxed, comfortable experience for the research participant. An excellent home-health nursing service focuses on the research subject, having a positive experience, and then use that feedback to refine service delivery approaches continually. In other words, it is not enough to simply be a referral service that calls up a home-health nurse to collect the blood. Home-health services need to tune into what the research subject’s needs are and tailor the service to those needs.

, MBA, MSF, is a thought leader and expert in the application of business analytics toward clinical trials, and Editorial Advisory Board member for and regular contributor to 

Firma Clinical Research CEO Michael Woods shares why COVID-19 may force greater efficiency for trial designs and greater access for trial participants.

Clinical Trial At-Home Service Providers

J&J strikes vaccine deal with U.S. Government

A compilation of recent notable news developments that pertain to the clinical trials industry.

Applied Clinical Trials-08-01-2020

Integration of Biomarker Validation in Oncology Trials

Immunomodulators and Cancer Research

COVID Exposes the Cracks in Trial Problems

The RACE for Children Act Takes Effect This Month

Designing Cell Therapies to Target Solid Tumors

Applied Clinical Trials, August 2020 Issue (PDF)

The Importance of Biomarker Management

Clinical Trials Can Duck the European GMO Problem

Clinical Trial At-Home Service Providers

News Notes

Initial Design Considerations for Immuno-Oncology Trials

Regulatory Collaborations Aim to Speed Access to New Vaccines and Drugs

Patients Are at the Heart of Cell and Gene Therapy