In this section
16 min read
Angela Qu, MD, PhD
How to select optimal endpoints for rare disease trials
8 min read
Five strategies for success in complex, innovative rare disease trials
Jamie L. Kistler, PhD
Thought partnership: How rare disease drug developers can engage with patient advocacy groups
6 min read
Study design and execution for rare diseases
Designing and executing rare disease clinical trials poses unique challenges. There are fewer patients, many are children, knowledge of the condition may be incomplete, and fewer sites can administer complex treatments such as cell and gene therapies—to name just a few. This section includes advice and lessons learned on selecting optimal endpoints, implementing complex, innovative trial designs, and engaging with patient advocacy groups to make it easier for patients to participate in clinical research.
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Claire Booth, MBBS, FRCPCH, MSc, PhD
How sites manage pediatric gene therapy trials
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How to Design and Execute Studies for Rare Diseases
Angela Qu, MD, PhD Senior Vice President of Biomarker Genomic Medicine, Parexel International
An expert in biomarkers, genomics, precision medicine, and innovative trial design and execution, Angela has more than 25 years of experience in a broad range of therapeutic areas, including oncology, immunology, CNS, metabolic, and rare disease drug development. She has led genomics- and biomarker-based development projects from the preclinical through late clinical stages. She is a core member of Parexel’s Oncology Center of Excellence and Rare Disease Working Group and has published more than 50 peer-reviewed journal articles on translational medicine and drug development.
Selecting the right endpoints to establish clinical benefit is one of the most challenging aspects of rare disease drug development. The starting point for determining relevant and sensitive efficacy endpoints is understanding the etiology of the disease and the drug’s precise mechanism of action (MOA). But with rare and ultra-rare diseases, often little is known about the condition’s natural course, and the experimental agent’s MOA may not be fully elucidated. Patients are often difficult to locate, making it hard to power a study adequately enough to measure treatment effects. Identifying the optimal endpoints for rare and ultra-rare diseases takes a lot of work. Based on my experiences in this fast-evolving field, I can offer some advice on how best to do it:
In my experience working with sponsors, they often face a situation where there are many possible endpoints, but it’s unclear which are the most meaningful. In this scenario, the task is to identify the optimal endpoints. Recently, a sponsor approached us with a complex case: they were developing a treatment for a rare autoimmune disorder with progressive neurologic phenotypes affecting patients’ motor function. This chronic condition systematically damages the peripheral nervous system, offering many potential objective and subjective endpoints to measure the impact of the drug on the loss or alteration of function. But which endpoints were optimal clinically and statistically? And which were the most meaningful to patients? There is no gold standard for endpoints in this disease. We took a multidisciplinary approach to solve the dilemma. Our medical experts interviewed key opinion leaders (KOLs) on scientific and medical aspects of the disease, conducted a thorough review of published literature, and analyzed the briefing documents of approved drugs in similar indications and information about failed drugs. After exhaustive due diligence, we proposed a data-driven set of clinical endpoints optimized for the experimental agent. The sponsor is incorporating these into the trial protocol. To find the optimal endpoints for a rare disease trial, conduct thorough and cross-disciplinary due diligence on the condition. Endpoint selection should be science- and data-driven and reflect patients’ priorities whenever possible. Don’t settle for relevant or convenient endpoints; they may not be optimal.
Endpoint selection needs to proceed from a thorough understanding of the heterogeneity of patients and disease expression across different age groups that will be studied in a trial.
Angela Qu, MD, PhD Senior Vice President, Biomarker Genomic Medicine, Parexel International
Clinical Development
Seek optimal endpoints, not just relevant or convenient ones
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Parse the rare disease patient population thoroughly
One of the most common problems I encounter working in rare diseases is the lack of a thorough, in-depth scientific understanding of the condition’s genetic target and complex mutation profiles. This can lead to treating the wrong patient group because of insufficient patient subcategorization or suboptimal biomarker testing. For example, research shows that more than 80 percent of rare diseases are genetic, and about 50 percent affect infants and children. In this setting, endpoints often need to be customized by age group and genotype or phenotype. And companies should stratify the patient population: for example, patients under two years old, patients aged 3 to 12, and adolescents represent heterogeneous subpopulations that may require different age-appropriate endpoints and cutoffs. Further, patients in different age groups suffering from a rare disease will be at different stages of disease progression and likely harbor different subtypes of genetic profiles. Endpoint selection needs to proceed from a thorough understanding of the heterogeneity of patients and disease expression across different age groups that will be studied in a trial. For example, recently, we worked with a sponsor developing a gene therapy for a rare musculoskeletal disease. The due diligence assessment revealed that the rate of ambulatory decline varies for these patients by mutational subgroup. We collaborated with the sponsor to establish different clinical endpoints, cutoffs, and biomarkers tailored to the targeted patient subgroups in the study. Further, how feasible and practical will it be to capture and assess the chosen endpoints in each age group at investigative sites, clinics, or remotely? The answer is critical to endpoint selection in clinical study design and in quality implementation.
Work with regulators to co-develop and validate endpoints
Sometimes, developers face a situation where there are no verified endpoints or existing measures of a disease due to its rarity. In this scenario, they will need to develop a novel endpoint, defined as one which has never been used to support drug approval or has been substantially modified from existing ones. Fortunately, regulators understand that developers struggle to identify and validate endpoints in rare and ultra-rare diseases. In October 2022, the FDA launched its Rare Disease Endpoint Advancement (RDEA) Pilot Program to support novel endpoint development and help sponsors qualify endpoints that have “never been used to support drug approval.” About five months earlier, the agency launched its Accelerating Rare disease Cures program (ARC), which also addresses endpoint selection, among other challenges. The RDEA pilot program represents an excellent opportunity for developers with an active pre-investigational new drug (IND) or IND program for a rare disease that want to use novel endpoints. They can submit their proposal for an opportunity to work closely with regulators and benefit from advisory discussions and direct advice from the FDA. The agency may also consider endpoint proposals for a natural history study if it is to be conducted in a rare disease or for a common disease if there is sufficient justification that the endpoint could apply to a rare disease. Proposal submissions will start on July 1, 2023, and only one applicant per quarter, up to a maximum of three per year, will be selected through 2027. This pilot initiative offers a new pathway that envisions sponsors collaborating with regulators, patient groups, thought leaders, and other stakeholders to drive novel endpoint development.
Conduct correlation analyses to validate a novel biomarker or endpoint
In rare diseases, many endpoints, such as patient-reported outcomes (PROs) for how a patient feels or functions, are subjective. In contrast, a biomarker endpoint is an objective measure. At Parexel, we conduct biomarker and endpoint evaluation and qualification. For example, correlation analyses between the biomarker and subjective measures can assess whether either or both are valid for rare diseases and rare types of common diseases. Correlation analyses require computational biologists and statistical geneticists who understand the biomarker data, genetics, and clinical conditions. Often, the data are "dirty" and incomplete, complicating the analysis. But these analyses are crucial to validating biomarkers or endpoints: developing a treatment using a non-validated biomarker will likely end in regulatory failure. At Parexel, we have successfully conducted biomarker and endpoint evaluation and development in clinical trials. Over the past 18 months, our biomarker and genomic medicine team has supported more than 300 biomarker and endpoint analysis projects for sponsors, ranging from genetics-genomics assessments to biomarker-endpoint analyses and validation. Recently, we helped a sponsor select and assess candidate biomarkers for their drug development program. Our findings established the value of and evidence for an objective surrogate biomarker endpoint in disease progression monitoring and drug responses.
Ensure accurate interpretation of complex genetic testing data in trials
The misinterpretation of highly heterogeneous genetic profiles or biomarker testing results, especially in global studies involving multiple laboratories and personnel, can lead to missed or mistaken patient enrollment. Once a sponsor has defined the mutational profile of the target patient population, the clinical operations team must administer genetic tests and interpret complex results to ensure that only eligible patients enroll in a study. A common problem at this stage of development is choosing non-qualified laboratories or assays to analyze the samples. At Parexel, we have dealt with the diverse reporting standards for genetic testing in numerous trials. We’ve learned that reading these reports requires specialized expertise. The documents can be more than 10 pages and there is no straightforward line related to the trial’s entry criteria. Site staff must scrutinize the entire report and frequently need to consult a genomic expert for conclusive recommendations on patients with ambiguous and complex genetic readouts. Recently, a company developing a drug for a rare genetic pediatric indication asked for our support in reviewing and interpreting genetic findings because they had past instances of enrolling ineligible patients. For global trials, additional complications are caused by translation issues and the lack of harmonization in testing results. At Parexel, when we take on a trial that targets a small genetic slice of a patient population, it’s our best practice to always conduct robust site training because sites are critical to this process. They need access to our biomarker and genomic medicine experts.
In our biomarker genomic medicine practice, we start the conversation very early with large pharma and emerging biotech sponsors. Often we begin with a one-page study concept for a clinical trial protocol and add design features using a data-and evidence-based approach. We leverage natural history data, registry data, genomic and biomarker data, and real-world evidence to compile all the knowledge available for the study design and endpoint selection. To overcome the obstacles because of different rules about accessing data in non-U.S. countries, we also increasingly access data through partnerships, fee-for-service arrangements, electronic medical record databases, and data mining to add insights to biomarker and patient selection.
Rare Disease Research
SOURCE: https://www.nichd.nih.gov/newsroom/resources/spotlight/020116-rare-disease-day
There are approximately 10,000 rare diseases known today.
80%
About 80% of rare diseases are genetic
50%
About 50% of all rare diseases affect children
A disease is considered rare in the United States if it affects fewer than 200,000 people.
NICHD
Selecting optimal endpoints
Randomized, controlled trials (RCTs) can measure the efficacy of a single treatment in a single disease indication with maximum rigor and minimum bias. However, RCTs are often impractical for rare and ultra-rare diseases: only a small number of patients are available, the condition may be highly variable or poorly understood, and using placebo controls for rapidly progressive fatal illnesses is not ethical. By contrast, a complex, innovative trial design (CID) can answer multiple questions about one or more compounds in one or more conditions or patient subgroups. Prespecified, “adaptive” modifications of the trial protocol can allow changes during the study based on interim data analyses. These adaptations can include sample size adjustments, dropping arms because of futility or safety findings, or enriching the target population. CIDs are well suited to rare diseases. They are efficient (enroll patients quickly), informative (yield more data about a treatment’s effects), and ethical (patients may be less likely to receive a placebo). They are also more complicated, costly, logistically challenging, and at greater risk of operational and analytical bias. At Parexel, we’ve found that innovative trial designs with adaptive elements are a demanding team sport. They require tight collaboration between biostatisticians, clinical operations, data management, medical experts, and project leadership. We’ve conducted dozens of CIDs, including more than 30 “basket” trials (which test one drug in multiple conditions), and we’ve learned from experience what works and what doesn’t. While some of our advice is common sense, many companies and clinical research organizations (CROs) struggle to execute these best practices with consistency and discipline. Here are five of them:
Review Risks
Clean Data
Give Sites Support
Closely Track
Plan Enough
Review risks for each cohort and across cohorts weekly
A master protocol can evaluate more than one drug in more than one patient population, and a basket trial can include several studies in one. But the risk management plan must be tailored to each indication or cohort. For example, if one arm enrolls pediatric or elderly patients, it will have risks specific to that cohort. A complex design involves running several trials simultaneously rather than sequentially, and it complicates risk review logistics exponentially. At Parexel, a dedicated project risk lead oversees initial and ongoing risk management activities using a system-based risk assessment and categorization tool (RACT). The initial assessment identifies Critical to Quality (CtQ) factors essential to data integrity and patient safety for each trial cohort. Some CtQ metrics are specific to adaptive trial designs. For example, if the early withdrawal rate escalates, it can compromise the sample size and render results uninterpretable. If one or more cohorts of a trial expand to enroll more patients, there is a risk that newly enrolled patients won’t meet the inclusion criteria. Once risk metrics are defined, we develop an integrated risk management and mitigation plan that looks at each cohort separately and then at the overall picture. The centralized statistical data analysis plan focuses on key risk indicators (KRIs) and quality tolerance limits (QTLs) for adaptive trials. Risk management proceeds on a set schedule throughout the trial, and the RACT includes prespecified remediations if a risk emerges. Though the frequency of review is set at the study start, there is room for re-evaluation and flexibility. For adaptive and rare disease trials, reviews are typically performed at least once per week and more often, if needed, for each cohort and for the entire trial.
Clean data continuously
We’ve found that the traditional approach to data handling, which involved gearing up the analyst team to “clean” data before the database lock, is obsolete for CIDs. Trials with adaptive elements require precise planning for the data that will be needed at each stage. That data must be monitored, analyzed, and cleaned on an ongoing basis. Throughout these trials, sponsors must communicate with independent data monitoring committees (IDMCs) so that they can review the data and make timely decisions about stopping, modifying, or expanding the study to a new indication or patient population. Continuous data cleaning requires tight coordination between data teams and clinical teams. At Parexel, we have adopted a data-cleaning approach that can deliver interim analyses to IDMCs with a minimal lag time after the last patient’s assessment. We have learned by experience that this is a prerequisite for IDMCs to make timely decisions. Smaller companies sometimes underestimate the data monitoring requirements of running an adaptive trial, and the frequent need for data cuts can quickly overwhelm their in-house staff. At Parexel, we find that only about 3% of data needs correcting or changing due to the source verification, data cleaning, and query process. Rather than deploying resources and expending effort on all the data, Parexel’s risk-based approach to data monitoring concentrates on critical factors, such as the project-specific QTLs and KRIs defined at the study’s start. We continually interrogate the data to spot emerging risks, mitigate them, and make decisions to protect the integrity of the dataset.
Give sites comprehensive and dedicated support
Trials involving multiple cohorts can be challenging for sites. We provide considerable logistical and emotional support to study staff when they are enrolling many cohorts for one trial at a single site. This support requires extra time from our clinical research associates and project leads. Complex trial designs demand a more complex project management structure from sponsors and CROs. For example, one Parexel client—a gene therapy company running a complex study in a rare disease—recently chose to retain an extra study coordinator assigned full-time to a single site to support the staff and avoid delays. As a result, they completed their study on time. Before a CID trial begins, we determine what each site will need and set up a logistical infrastructure to give it the training and support for a successful trial. For example, one site might enroll pediatric and adult patients in separate arms in a rare disease multi-cohort study. The risks, doses, data collection schedules, informed consent materials, and other study documents will differ between the arms. We recently ran a trial with 14 cohorts, all of them in different cancer indications. Sites had to accommodate the different assessment schedules and dosing regimens while administering different standards of care based on the condition. Each arm of the trial had a specific risk management plan, and sites received support tailored to the cohort (or cohorts) they were enrolling and treating.
Give Sites Suport
Closely track and manage patient onboarding
Patients with rare diseases often have rapidly progressive, terminal conditions. They are motivated to participate in a trial as soon as they qualify. For many, the trial represents the only treatment and follow-up care they will receive. And due to the small patient populations in rare disease trials, every patient’s data is much more valuable. Sponsors cannot afford to let problems with paperwork, site training, translation services, or study supplies disrupt patient enrollment and treatment. Knowing when you can onboard each patient into the study is critical, and there should be no delays. At Parexel, we track the allocation of patient “slots” in each trial to achieve a streamlined progression from qualification to informed consent to the first treatment. We liaise with sites to project the timing accurately. We always have backup patients ready to fill in if a patient or site must change the schedule. In this way, we avoid disappointing patients and principal investigators (PIs), who have likely made promises to their patients about when they can join the trial. We recently worked on a Phase 1 trial with three patient slots available for the first cohort. The sponsor and primary PI did not obtain Institutional Review Board approval on time at the site slated for the third and final slot. The patient lined up to take that slot was thus unable to enroll, and a patient from a different site enrolled instead. To address the PI’s and patient’s frustration and maintain a good relationship with the site, we rearranged the slot assignments and placed the site in line for the fourth patient slot in the trial once the IRB approval was in hand. It is critical to have the paperwork done on time and plan carefully to solve problems as they arise.
Plan enough drug supply for every protocol permutation
Adapting a protocol to include a new arm or expand an existing arm can cause drug supply shortages, especially for expensive products with complex manufacturing procedures or limited supply. Recently, we conducted a trial in which a sample size re-estimation added 20 percent more patients. Unfortunately, the sponsor had not arranged for a sufficient quantity of drug to be available, and it was impossible to expand the trial immediately. Frequent protocol changes require flawless supply chain logistics to avoid delays and disruptions in patient recruitment due to inadequate drug supplies. At Parexel, we scrutinize the drug supply plan of every protocol to ensure that, before the first patient enrolls in a trial, the drug supply will be adequate to cover every potential adaption of the protocol.
Steve Winitsky, MD Vice President, Technical, Parexel International
Thought partnership: How rare disease drug developers can engage with patient
Martin Roessner Corporate Vice President, Biostatistics, Parexel International
Authors
Jamie Pierson Project Leader, Parexel International
Ginny Birkhead, RN, BSN Senior Clinical Operations Leader, Parexel International
Almost nothing we have described in these best practices is brand new. But in the exceptionally challenging environments of rare diseases and complex, innovative trials, errors, and oversights can quickly compound into costs, delays, and disappointments. These five strategies, effected by an experienced team with discipline and rigor, can keep a trial on track.
Martin brings over 40 years of experience in biostatistics for Phase I-IV drug development from his 34-year tenure overseeing product submissions at Sanofi- Aventis (and its predecessor companies). Since 2010, he has led Parexel’s global biostatistics services, supporting the planning and execution for all drug and device development phases, including regulatory meetings and submissions. Martin has supported numerous successful product marketing applications, negotiated labeling changes, and managed interactions with many of the world’s foremost health authorities. He received an M.S. in mathematics and biostatistics from RWTH Aachen University.
Jamie has more than 10 years of experience in the biopharmaceutical industry, primarily in clinical research and technology. She spent her first five years in the industry developing interactive response systems, many of which were for complex cohort and adaptive trials. Jamie’s primary therapeutic area of expertise is neurology, specifically rare pediatric genetic disorders. She has managed rare-disease trials in Duchenne muscular dystrophy, Leigh syndrome, mucopolysaccharidosis, and giant axonal neuropathy.
Ginny has spent more than 20 years in the biopharmaceutical industry, focusing primarily on clinical research, drug safety, and pharmacovigilance. She is familiar with all phases of the drug-development process and well-versed in global clinical-research guidelines and regulations. Her therapeutic areas of expertise include oncology, cardiology, neurology, and autoimmune and infectious diseases. She has worked on rare-disease trials in spinal muscular atrophy, myasthenia gravis, and thyroid eye disease and has managed rare disease-gene therapy trials in pediatric and adult patients.
Emerging biotechs often struggle to execute CIDs in rare diseases
Locating and enrolling enough patients. Providing realistic development timelines to investors. Running out of money to fund the entire trial. These are some of the challenges emerging biotech companies often face in executing CIDs. The solutions to these problems require expert planning. At Parexel, we’ve helped clients design trial protocols with interim analyses at predetermined milestones to allow further fundraising for the next milestone. We’ve also helped them estimate how many patients with rare or ultra-rare diseases they must enroll to meet the regulatory requirements for evidence generation. And, based on our experience designing and running CIDs, we’ve helped create data-driven projections of study start-up, enrollment, treatment, and follow-up times for companies that must gain approval from a Board of Directors or Scientific Advisors.
Recent FDA guidance documents and resources for complex, innovative trials
Extension of Complex Innovative Trial Design Program (October 2022)
Topic
Document
Final Guidance on Master Protocols (March 2022)
Complex Innovative Trial Design (CID) Paired Meeting Program
Master Protocols: Efficient Clinical Trial Design Strategies to Expedite Development of Oncology Drugs and Biologics
Expansion Cohorts: Use in First-in-Human Clinical Trials To Expedite Development of Oncology Drugs and Biologics
Complex, innovative trial designs
Jamie L. Kistler, PhD Senior Director, Customer Strategy, Medical Communications, Parexel International
Jamie has more than 15 years of medical communications experience, and over a decade of clinical writing experience. She is a member Parexel’s Cell & Gene Therapy Working group, based on direct experience with gene therapy products. Her extensive therapeutic expertise includes rare diseases, and she is a faculty member for the International Society for Medical Publication Professionals (ISMPP) and Co-Lead of the Medical Affairs Professional Society (MAPS) Patient Centricity Working Group.
Parexel experts and former senior EU regulators share the regulatory challenges sponsors must understand to navigate the EU’s orphan drug designation process and gain authorization.
If you’re going to work with rare disease patients, invest in being a good thought partner - take the time to do it right and understand the needs of the patient population in terms of daily logistics, dietary requirements, and coordinating care for not only the rare disease patient but for their whole family.
What do PAGs want from drug developers?
Patient advocacy groups (PAGs) play a vital role in helping companies design rare disease studies that are convenient, transparent, and humane for patients, caregivers, and families. However, companies must engage with PAGs as thought partners from the earliest stage of development to achieve the optimal clinical trial design. Too often, companies turn to PAGs as a last resort when trial recruitment fails rather than approaching them as partners from the early study concept stage. When PAGs, clinical research organizations (CROs), and biopharmaceutical companies engage in a sustained and meaningful dialogue, they create opportunities for patients to participate all along the drug development journey. We asked Parexel experts Pam Rattananont and Julie Shutt to share their thoughts and experiences on how companies can form effective long-term partnerships with rare disease PAGs.
Kistler: PAG organizations in the rare disease space are extremely savvy and want partners with the same sense of urgency to provide treatments for their patient communities. They know how drug development works. At annual industry and patient advocacy meetings, educational sessions teach PAGs how to form biotech firms and fund their research. Patients and caregivers want to work with sponsors. Still, they get frustrated when they provide data and money, and the sponsor decides to change direction or rebalance their portfolio for business reasons. That can be challenging for patients and parents, especially when dealing with rapidly progressive diseases. Sometimes, PAGs go directly to researchers, bypassing companies, and fund the research themselves. They are learning how to attract investors and drive clinical development programs.
How can PAGs help drug developers?
Kistler: PAGs can give sponsors insights into endpoints that reflect patients’ quality of life. Many patients are looking for therapies that will reduce the burden of their disease: If they don’t have to go to the emergency room as often, or if their child has 50 seizures a month versus 100, that’s a win for them. One recent example is an emerging biotech company developing a drug to treat a rare neurological disorder. They used real-world data gathered from a patient-consented medical records platform to bolster an investigational new drug (IND) filing. Based on these data, the FDA removed an initial clinical hold on the IND. That’s how valuable patient data and collaboration can be for developers.
What are some best practices for collaborating with PAGs?
Kistler: If you’re going to work with rare disease patients, invest in being a good thought partner. Take the time to do it right and understand the needs of the patient population in terms of daily logistics, dietary requirements, and coordinating care for not only the rare disease patient but for their whole family. Often these patients have rapidly advancing diseases and very little time. I remember one trial where the sponsor did not do proper due diligence and didn’t understand that the target patient population was on a special diet. They developed a drug formulation that infringed on dietary restrictions. So, after enrolling patients and raising their hopes of an effective treatment, the sponsor had to halt the trial and start over with a new formulation.
What are common mistakes to avoid when working with PAGs?
Kistler: Don’t overstate what an experimental agent can do or downplay the risks, of which there are many. For example, gene therapies only work on a small subset of a rare disease population. Even if patients have the relevant mutation, they may have an additional mutation that excludes them from a clinical trial. Patients’ emotions and hopes are sky-high, so the messaging needs to be accurate, science-based, and comprehensive, not aspirational. Also, cell and gene therapies (CGTs) are still so new that many patients don’t understand the treatments or follow-up requirements. Even physicians may not understand CGTs, and the level of awareness and access can vary tremendously by country. At Parexel, we have a team of in-house CGT experts who support our work with sponsors, PAGs, and the healthcare community to help them with appropriate information and manage expectations.
Why are we seeing so many premium-priced rare disease drugs coming on the market?
Kistler: PAGs can give sponsors insights into endpoints that reflect patients’ quality of life. Many patients are looking for therapies that will reduce the burden of their disease: If they don’t have to go to the emergency room as often, or if their child has 50 seizures a month versus 100, that’s a win for them. One recent example is an emerging biotech company developing a drug to treat a rare neurological disorder. They used real-world data gathered from a patient-consented medical records platform to bolster an investigational new drug (IND) filing. Based on these data, the FDA removed an initial clinical hold on the IND. That’s how valuable patient data and collaboration can be for developers..
Kistler: If you’re going to work with rare disease patients, invest in being a good thought partner - take the time to do it right and understand the needs of the patient population in terms of daily logistics, dietary requirements, and coordinating care for not only the rare disease patient but for their whole family. Often these patients have rapidly advancing diseases and very little time. I remember one trial where the sponsor did not do proper due diligence and didn’t understand that the target patient population was on a special diet. They developed a drug formulation that infringed on dietary restrictions. So, after enrolling patients and raising their hopes of an effective treatment, the sponsor had to halt the trial and start over with a new formulation.
Engaging with patients
Claire Booth, MBBS, FRCPCH, MSc, PhD Mahboubian Professor in Gene Therapy and Paediatric Immunology (UCL) and Consultant Paediatric Immunologist, Great Ormond Street Hospital (GOSH)
Professor Claire Booth has worked at GOSH since 2005. UCL Great Ormond Street Insitute of Child Health and Great Ormond Street Hospital are among Europe’s leading institutions in children’s health research. She conducts clinical research and provides clinical care for inpatients and outpatients. She is an expert in primary immunodeficiency (PID) and gene therapy and leads gene therapy clinical trials at GOSH for patients with immune deficiencies and hematological and metabolic disorders. She currently serves as the principal investigator (PI) of Phase I/II lentiviral clinical trials of hematopoietic stem cell gene therapy for ADA-SCID, X-SCID, LAD-I, p47 Chronic granulomatous disease and Fanconi Anemia, and co-investigator on other trials.
Sponsors must design trials to meet regulatory requirements and be convenient and relevant for patients. But what about sites? Principal investigators (PIs), nurses, study coordinators, project managers, and data entry technicians at sites work on the front lines of clinical research and patient care. Gene therapy trials are complex and, when they involve pediatric patient populations with a rare disease, feasibility is paramount. Yet these trials have produced exceptional results, transforming the lives of patients and families desperate for a cure. Academic clinician Claire Booth talks about the lessons she has learned at one of Europe’s largest and most experienced gene therapy research sites.
We’re a group that has worked together for many years with a consistent but agile structure. The research nurses, physicians, lab and manufacturing staff, project managers, and data managers operate as a team. We meet weekly to discuss our trials, for example, which patients are coming up for visits, what samples do we need, and when we are manufacturing products We are a well-oiled machine. We have gained a lot of practical experience over the past 15 years as a team and are constantly learning, adapting, and improving.
We’re a group that has worked together for many years with a consistent but agile structure. The research nurses, physicians, lab and manufacturing staff, project managers, and data managers operate as a team.
Market Access
The key to success is teamwork
The biggest challenges are not necessarily clinical
Project and data management often pose greater challenges than clinical or patient-related issues. Our project managers provide tremendous regulatory support. They manage protocol amendments, sponsor monitoring visits, data audits, trial infrastructure issues like eCRFs, and sample shipping. Cell and gene therapy trial protocols often have as many as 10 or 15 amendments, requiring significant paperwork and attention to detail from project managers.
Patient needs must be considered
Patient-reported outcome (PRO) measures are a very topical subject across countries. Too often, PROs have been a tick-box exercise in clinical trial design and approval. Regulators and payers routinely ask trial sponsors whether they have included PROs in their trial design. However, a deeper dive is required. Do the chosen PROs capture relevant information for the patients and families? In discussions with patient advocacy groups (PAGs), I’ve heard from parents that ‘classical’ trial outcome measures may not mirror what is essential to their children’s lives. For example, if a child has a blood disorder with low platelet counts and is at risk of bleeding, the child and parent may not value the trial’s primary endpoint of a normal platelet count. They may care more whether the child can play a sport or go to school without worrying about having a major bleed. Regulators often insist on definitive evidence in the form of a number, a level that is or is not reached. That’s understandable, but it may not capture data crucial to a patient’s quality of life. Trial designs have not adequately incorporated patients’ and caregivers’ perspectives in the past, but this is changing.
Remote patient monitoring has limits
Remote patient monitoring offered a positive revolutionary change for patients, and it can be. But we can sometimes miss important clinical data when we lose the physical connection with our patients. Face-to-face interactions are still valuable, particularly early in a study. Post-COVID, though, patients have become used to this approach and like that they can be ‘seen’ in their local center and maintain contact with the trials team. They prefer the remote approach because it reduces the burden of participation. But caring for a patient is about more than blood samples or data trends. It’s about their quality of life, the quality of their family life, and general health. It’s challenging to capture a genuinely holistic approach via video or telephone. This is true for trials and general checkups. You may see a patient face-to-face for the first time in a year and say, how long have you had that lump on your neck? And the patient says what lump on my neck? And that lump could represent a significant health problem. You don’t get the detail of how a patient is doing remotely, even through completed patient diaries. Remote data monitoring also has limitations. Data monitors want to speak to the people doing the data entry and the PIs and nurses dealing with patients in person. If a monitor spots a recurrent problem, it’s often easier to sort that out face-to-face and get to the root cause.
Patients deserve better communication
Patients find the lack of communication between clinical trial sites, sponsors, patients, and PAGs frustrating. They feel a lot of effort goes into the startup of trials, with a flurry of activity to boost recruitment and build excitement. And then they don’t hear updates for 6, 12, or 24 months. They might even read about developments in the newspaper before they hear anything about the results of the trial they enrolled in. So we’ve moved patient communication higher on our agenda. Patients should not find themselves in an information vacuum.
Site management
Monitoring can be challenging for sites
Preparing for monitoring visits from sponsors and responding to the feedback we receive contributes significantly to the team's workload. Project managers, research nurses, investigators and data managers often have to set aside a lot of time for this. I don’t know how to alleviate this problem, but different solutions may work for different sites. For example, having more frequent monitoring visits could reduce the number of queries per visit, so work is more spaced out, allowing time for other projects. However, this can sometimes feel like a visit every other week. If you space out the visits by three or six months, site staff may need to spend more time sitting with monitors to review data and answer queries, which may not suit a team either. One solution that has worked—but is not always possible—is a dedicated data manager with exhaustive knowledge of the trial protocol and case report forms. That person sits with the monitors, leads them through the data, and resolves the queries in real time.
