1. Can you please introduce yourself, explain your role and tell us about the mission of the Forum for Collaborative Research, particularly the Transplantation Associated Virus Infections (TAVI) forum.
I am Veronica Miller, an immunologist with a PhD and an expert in “regulatory science” with over 24 years of experience currently working at the Forum for Collaborative Research, and before that, at the Frankfurt HIV Outpatient Clinical Research Centre. The latter exposed me to drug development in action during the earlier days of antiretroviral treatment for HIV infection. It was the perfect incubator for my subsequent career as Director of the Forum for Collaborative Research, a program at UC Berkeley School of Public Health, with offices in Washington, DC and Berkeley. The mission of the Forum for Collaborative Research is to facilitate drug development through collaborative interactions between pharmaceutical and diagnostic companies, clinical researchers, regulators, and patients, in areas of unmet medical need. We support consensus and collaborative analyses, including a unique industry data sharing platform. The TAVI Forum applies this mission to research on cytomegalovirus (CMV), adenovirus (ADV), BK polyomavirus (BKPyV), and herpesviruses in immunosuppressed patients, primarily, transplant patients.
2. As someone who works at the intersection of academic and industry clinical research, patients, and regulators, what are the biggest challenges you see in drug development?
Drug development and regulatory landscapes are constantly evolving. The field is adapting to scientific breakthroughs through better understanding of disease processes, new technologies such as whole genome sequencing, new therapeutic approaches (gene editing and epigenetic interventions, mRNA based vaccines, cell-based therapies) and the application of AI and ML to data analysis, physiological monitoring, external controls, and much more. The rapid advancement of innovation challenges global systems including research networks (how to bring the latest innovation into remote/less advanced regions), regulatory authorities (how to keep up with the latest science/technology to base regulatory decision making on sound scientific and ethical principles), and societal responses (understanding what the “new” means for individual and public health).
As we move away from the age-old and reasonably well understood “gold standard” of placebo (or standard of care controlled, large clinical trials for common diseases including (cardiovascular disease (CVD) and Type 2 diabetes (T2D)) to smaller indications, such as those encountered in the transplant settings, unfamiliarity with innovations in analytics and statistics to address bias can be a stumbling block across sectors and stakeholders. On the whole, I think that as a field, we need to retain scepticism with respect to new approaches, but we need to increase the efficiency of learning how new methods (e.g. causal inference) work, how they compare to each other, and how to deal with remaining uncertainty. This requires a commitment to collaboration, removing blocks to data-sharing, complete transparency and accountability. No single company – no single sector – can do this on their own.
3. TAVI specifically focuses on areas with significant unmet medical need. What makes transplantation particularly challenging from a drug development perspective, and why is collaboration essential?
To me, the transplantation setting is one of, if not the, most complex medical settings. A transplant recipient is generally critically ill and a genetic chimera with two distinct medical histories, specifically, exposure to viruses (e.g. CMV) and levels of immunity. Adding significant immunosuppression into the mix requires careful monitoring of recipient and donor derived cells/organs, virologic activity, and respective immunities. A major challenge is the lack of standardization of procedures and assays across transplantation settings within countries and across the globe. Trials need to be multi-centric and multi-national to recruit adequate number of patients, highlighting the non-standardization problem. Collaboration is needed at many levels: standardized definitions of disease stages, identification of biomarkers that maybe fit-for-purpose as endpoints, and validation of these biomarkers (that they are solid predictors of treatment response as defined by clinical benefit) to name a few.
4. Why is it important to standardize the measurement of disease progression across studies and how important is it to incorporate perspectives from the transplant community?
There can be subjectivity in how clinical disease progression is ascertained, which makes cross-study comparison very difficult. This includes whether are biopsies done, if so, when, and how are they quality controlled, whether fever is adequately assessed, and whether the pathogen quantified at the right intervals. In a field like transplantation, we should be able to learn from clinical practice, but the learning is often limited to what colleagues learn within one centre or institution. Conducting meta-analysis is frequently a non-starter, because of lack of assay standardization, and threshold values used for intervention decision making. Furthermore, clinical centres and their staff are usually not set up to gather data in a manner suitable for regulatory purposes. Thus, drug developers have to start from scratch in many cases.
The perspectives from the transplant community (and here I include the patients, their families, and their clinical care givers), is important because their perception of how much benefit they stand to gain, and how much risk they are willing to be exposed to will determine their readiness to participate in clinical trials. Patients and their representatives can also make it clear that they support clinical research data sharing if helpful for accelerating drug development, meaning that other patients like them may have access to effective drugs sooner.
5. TAVI serves as a neutral, objective platform for data collaboration. Why is this type of transparent, unbiased input necessary in transplant medicine, and how does it differ from traditional approaches to drug development?
Traditional drug development features one drug developer (and occasionally a diagnostic partner) taking responsibility for generating all the data needed for the particular indication they are striving for. This includes generating evidence from real world data, if appropriate for the specific context. Any other developer working in the same disease area would have to duplicate these efforts, at great expense and time resources. It would benefit both developers to collaborate on establishing a good source of real world data to generate fit-for-purpose real world evidence to accompany their clinical trials, perhaps as a natural history study to model disease progression in absence of treatment according to the recipient and donor characteristics, or even as external controls in some situations. There are multiple ways something like this could be set up. Another source of good data would be collecting all placebo arm data from previously completed trials, to match the “natural history cohort” to patients undergoing inclusion/exclusion and the overall clinical trial experience.
6. For biotech companies developing therapies in transplantation, what advice would you give them to engage effectively with the broader transplant community and regulators throughout the clinical development process?
Regulators invite developers to meet with them “early and often”. However, in reality this is not always possible. Regulators from different regions often have different requirements and points of concerns regarding what constitutes “sufficient evidence” to propose a new biomarker to function as an endpoint. I have found that regulators are more often than not, quite willing to hear what the clinical and patient community thinks. Platforms such as the Forum for Collaborative Research allow such “informal” dialogues to take place in a non-binding fashion, and are a good source of information for regulators from around the world to hear each other’s concerns, thus of the patients, the clinical researchers and of course, the pharmaceutical and diagnostic developers. I would encourage biotech companies to find such opportunities – not only will they learn from larger pharma companies with more experience in the disease area, but also “hear” how science is being translated.
