Protocol Development #40
Over the last few weeks, it has been a pleasure to see increasing interest in the newsletter, interest that I hope reflects the change in the perception of what the study protocol is or can be - i.e., moving away from just the precursor to conducting a clinical study toward an integral and dynamic plan that combines ever-increasing expertise. In this newsletter, in order to provide some semblance of structure to a lot of overlapping themes, it is broken down into sections. Since it's inception, the number of sections has grown as new areas of research have matured. As always, feedback and suggestions are welcome - as an educational vehicle - the newsletter is only useful if it serves the needs of its audience. Happy reading!
Patient Engagement
[Article - Research] Morel et al published The value of co-creating a clinical outcome assessment strategy for clinical trial research: process and lessons learnt where they supported UCB pharmaceutical research programs by co-creating a COA strategy (i.e. PROs) for studies involving early-stage Parkinson's patients. To do this they used a two-stage strategy, 1) identify symptoms that are cardinal to the experience of living with early-stage Parkinson's, and 2) develop PRO instruments to better capture these symptoms. The output of this work contributed to a better conceptualization of what clinical benefit looks like for early-stage Parkinson's patients as well as highlighting shortcomings of 15 legacy PRO instruments. Interestingly, the UCB-patient organization partnership led to faster participant recruitment for studies as it gave access to pre-existing networks. I would also presume that by making the effort to engage with participants on what clinical benefit would actually look like - they signaled that they were taking participant feedback seriously - what would it take for you to participate in a study?
[Whitepaper] Clare Grace and others at Parexel provide guidance in the latest whitepaper on Achieving patient-guided drug development. In the article, Clare highlights the significance of what it means to engage patients in clinical studies:
"Developing patient-focused therapies is not a 30-minute meeting with patients or some text on a corporate website. It is a systematic and sustained approach that begins at the earliest stages of drug development and continues throughout the whole continuum."
The three approaches highlighted by Clare are:
Be it diversity, patient-reported outcomes, or designing studies for the patient - the resources give short overviews with high-level summaries.
[News] Moe Alsumidale recently reported on AstraZeneca Reveals New Clinical Trial Patient Burden Data - an exciting area of patient engagement that directly impacts the protocol. Understanding patient burden can help study teams understand the demands that their decisions regarding the schedule of activities (SoA) have on participants. By doing so, this can help focus decision-making on what's important to the participants - for example AZ's research found that older participants preferred on-site visits compared to younger participants, and Japan preferred home visits and deliveries compared to other geographies.
Process & Templates
[Article - Commentary] Messenbrink et al published Developing Generic Templates to Shape the Future for Conducting Integrated Research Platform Trials that summarized EU-PEARL's efforts to develop a platform study template (see PD#29 for links). During the 3.5 year work plan, the authors and team went through 3 draft versions before the final version was released. Although the final release was based on an older TransCelerate CPT (the most current at the time), there's hope that the next CPT release will incorporate the key structural components. Although the template falls short of being able to accommodate all master protocol designs, it does provide standards for one of the most challenging (platform studies), and thus a good start point on which the structural configuration can be based.
[Article - Research] Palm et al published Development, Implementation, and Dissemination of Operational Innovations Across the Trial Innovation Network where they discuss how to improve the quality and conduct of multicenter studies. Roadblocks and barriers include multiple pain points - notably for us flawed design and lack of stakeholder engagement are particularly relevant. Innovations in these areas include master protocols and adaptive designs, design labs, pragmatic designs (design) as well as enhancing site assessment and patient identification. Interestingly, as the initiative progressed, it became clear that significant work was being done in complementary areas - thus highlighting the need to align such efforts. Future directions look promising for protocol development since expanding the TIN toolbox would likely result in additional best practice efforts being disseminated.
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Clinical Study Design
[Article - Research] White et al published When should factorial designs be used for late-phase randomised controlled trials? that presents an interesting insight into infrequently used factorial designs. If you're new to study designs, or want to see what considerations should be taken into account when considering a factorial design approach, then this resource is worth reading. Points to consider include clinical elements (e.g., the risk of interaction), practical issues (e.g., risk of nonadherence), statistical issues (e.g., how to analyze outcomes), and external/other issues (e.g., regulatory limitations).
[Article - Research] Luo et al published ClinicalRisk: A New Therapy-related Clinical Trial Dataset for Predicting Trial Status and Failure Reasons - an interesting take on the age-old desire to know what the future impacts are from decisions made in the design stage. I don't pretend to understand the experimental approaches they made but what is interesting is efforts toward mining available data to predict the success rate of a study. Although this will likely take many years before we reach true predictability at a level that we'd need for protocols, every tool helps in trying to maximize the possibility that a study meets its objectives - regardless of whether the intervention is successful or not.
[Article - Research] Rohde et al published Practical and statistical considerations for the long term follow-up of gene therapy trial participants that gives insight into an increasingly common type of study - long-term follow up studies (there are a number of other names - the most common I've seen is "rollover study"). Using gene therapies as the example, the authors detail key design considerations. A few of the more novel considerations include using EHR data from patient registries, or establishing a master protocol for multiple LTFU studies for therapies with a commonality. Naturally, such measures present new and seemingly insurmountable challenges due to the lack of precedence. As the authors describe, how do you evaluate AEs across multiple programs using standard commonality definitions that are incompatible with small, rare, disease populations? Overall, the article provides details on how to aggregate and harmonize LTFU data - an important step if LTFU studies are to break into the mainstream.
Digital
[Article - Review] Harmon et al published The Digitization and Decentralization of Clinical Trials that takes a US-centric dive into digital advancements that have led to the digitization of studies and their decentralization. Overall, the review gives a great overview of both concepts and is a helpful resource for those looking to understand more about how digitization or decentralization can be applied to a study and - importantly - what should be considered for successful implementation.
[Article - Research] Chodankar et al published The role of remote data capture, wearables, and digital biomarkers in decentralized clinical trials where they published their India survey findings on DCTs. Overall, experience shows that for two thirds of respondents, <25% of studies were decentralized, with almost the same proportion reporting that wearable devices was the most common form of remote data capture. Key challenges include the financial impact of implementation, as well as unclear regulatory acceptance, and a lack of data integration. On a more positive note, the future looks bright as pharmaceutical organizations and CROs establish teams and partnerships to further implementation.
[Magazine] Adelina Paunescu published Budgets and Billing in Clinical Trials: DCT Considerations, outlining what can or should be done to reduce costs. Although there are 7 key areas, it's #2 that's of most interest to us as it relates to Protocol design optimization. Arguably, these are less DCT-related and more QbD related but nevertheless, increased precision on eligibility criteria, reduced data collection, improved quality (to mitigate the occurrence of avoidable protocol amendments), and better endpoints are the recommendations. Tying control arm participation to EHR data is the most DCT-related suggestion - although how that can be incorporated is unclear to me.
CIDs/Master Protocols
[Article - Case Study] Clarke and James published How to Compose Platform Trials that discusses how to design and execute a platform study by using their experience as part of the STAMPEDE study. Key lessons related to the protocol include
Webinars
MRCT are hosting an Joint Task Force for Clinical Trial Competency (JTF) Biannual Global Meeting on Tuesday 14 November 2023 from 15:00 - 17:00 CET.
CTTI/FDA are hosting a 2-Day Virtual Public Workshop to Enhance Clinical Study Diversity on Wed 29 to Thurs 30 November 2023 from 16:00 - 20:00 CET.