Modernising clinical trials: The PARTICIPATE framework
Each year, a staggering 67 million individuals lose their lives.1 Heart disease account for approximately 17.9 million of these deaths,2 and cancer takes away 10 million lives.3 This year alone, 42.9 million4 souls have sadly departed, and the global mortality clock continues to tick.
Amidst these alarming mortality figures, with heart disease and cancer leading the charge, clinical trials emerge as a glimmer of hope. These trials, pivotal in advancing medical research, have unfortunately been marred by a disheartening success rate. A mere 13.8% of drugs5 that enter clinical testing eventually see the light of day, gaining approval for public use.
Challenges facing clinical trials
This low success rate stems from myriad challenges. At the forefront is a glaring lack of participant diversity, which often skews results and limits the applicability of findings to broader populations. Coupled with this is the persistent hurdle of patient enrolment, a challenge that underscores the need for better outreach and engagement strategies. Additionally, the modern era of medicine generates vast amounts of data at an unprecedented rate. Yet, the capability to process this data swiftly and efficiently often lags, leading to potential oversights and delays. The financial aspect further complicates the landscape, with the exorbitant costs of trials often limiting their scope and reach. Furthermore, the intricate web of regulatory variations across different countries adds another layer of complexity, necessitating a harmonised approach to ensure consistency and compliance.
Amid these challenges, the introduction of modern technologies, such as artificial intelligence (AI), wearables, and telemedicine, has generated cautious enthusiasm. While these technologies have made significant inroads in certain areas of clinical trials, there remains ample room for further exploration and integration. The incorporation of these technologies into clinical trials, though promising, is an ongoing journey. This gap between potential and current utilisation emphasises the importance of a more integrated approach to leveraging these technological advancements. Beyond just individual technologies, there's an imperative to refine the entire clinical trial process. This refinement aims to address the existing challenges and to establish a framework that prioritises patient outcomes, maximises engagement and safety, and proactively minimises risks. With the challenges at hand, the PARTICIPATE framework stands as a pivotal solution, making clinical trials more robust, patient-centric, and efficient in delivering their intended outcomes.
The PARTICIPATE framework: A paradigm shift
The PARTICIPATE framework is not just another methodology; it's a clarion call for a paradigm shift in how clinical trials are conducted. PARTICIPATE proposes the following key pillars to modernise clinical trials holistically:
- P — Patient-centric approach
- A — Accessibility & affordability
- R — Real-world evidence
- T — Technology integration
- I — Inclusion & diversity
- C — Collaboration
- I — Innovative endpoints
- P — Planning & proactive risk management
- A — Adaptive design
- T — Training & education
- E — Ethical standards & data privacy
At its core, it champions a patient-centric approach, ensuring that the voices, needs, and experiences of patients are not just heard, but actively shape the trial. This approach promises outcomes that resonate deeply with the patient community, fostering better compliance and reduced dropout rates.
P — Patient-centric approach
Historically, clinical trials have prioritised scientific objectives, often at the expense of patient experiences and needs. However, a shift towards a patient-centric approach is not just about empathy; it's also about efficacy. When patients feel heard and their experiences are integrated into the trial design, the results are more actionable, robust, and safe for adoption.
For example, in a hypothetical Phase II trial for a new breast cancer drug, a digital platform can be employed to gather daily feedback from participants about their side effects and overall well-being. If, for instance, researchers were to notice a pattern of severe fatigue reported by a significant number of participants within the first week, the real-time feedback would allow for adjustments to be made to the drug dosage. This could potentially alleviate the fatigue, while maintaining the drug's efficacy against the tumour. Such immediate communication ensures that the trial remains both scientifically sound and responsive to the genuine needs of the patients.
A — Accessibility & affordability
The benefits of clinical research should not be confined to a privileged few. Accessibility and affordability are crucial to ensure that a diverse range of participants can benefit from and contribute to clinical trials, making the findings more universally applicable.
For example, the deployment of mobile clinics to remote areas can help enhance accessibility, address affordability challenges, and foster diversity. These clinics can bridge the geographical divide, ensuring that participation in trials isn't limited by location.
R — Real-world evidence
While controlled environments are a hallmark of traditional clinical trials, they sometimes fall short in mirroring the complexities of real-world scenarios. Incorporating real-world evidence provides a more holistic understanding of treatment effectiveness outside the confines of a clinical setting.
For example, wearable devices, like smartwatches, continuously monitor vital stats, providing a richer picture of a patient’s health. They can detect irregular heart rhythms or sleep patterns, offering insights that periodic clinical check-ups might miss. This continuous data stream helps researchers understand treatments' real-world impacts more comprehensively.
T — Technology integration
The fusion of cutting-edge technology with clinical trials heralds a new era of efficiency and precision. Tools like AI and wearable devices can not only streamline processes, but can also enrich data quality and scope. This holistic approach ensures comprehensive insights, fostering better patient outcomes and more informed medical decisions.
For example, Stanford developed EchoNet6 - an AI-driven system for analysing heart images, also known as echocardiograms. In clinical trials conducted by the team at Stanford, EchoNet traced the heart's ventricle more accurately than human sonographers, with cardiologists modifying only 1.3% of AI tracings compared to 3.1% of human tracings. This innovation ensures quicker and more accurate assessments, reducing manual errors and highlighting the benefits of technology in cardiovascular diagnostics.
I — Inclusion & diversity
For clinical trial results to be truly representative, it's imperative to have a diverse participant pool. Emphasising inclusion ensures that trials cater to the unique needs of various demographics, leading to more comprehensive and equitable healthcare outcomes.
For example, in a globalised world, language should not be a barrier in clinical trials. Multilingual materials can ensure that participants, regardless of their native language, grasp the trial's protocols and objectives, fostering inclusivity and diversity. A testament to this is the initiative by the Oregon Health & Science University (OHSU).7 While Hispanic/Latino individuals make up 15% of Oregon's population, they account for only 5% of participants in certain cancer trials. Recognising this disparity, Dr Eneida Nemecek at OHSU was awarded a grant to bridge this gap. Their initiative involves conducting forums with local Hispanic/Latino communities to understand barriers and knowledge gaps, launching an educational campaign about clinical trials, and hiring a dedicated nurse navigator fluent in Spanish. The goal is to double the participation of Hispanic/Latino patients in OHSU's cancer trials, ensuring that the benefits of clinical research reach all segments of the population.
C — Collaboration
The complexity of modern clinical trials necessitates a collaborative approach. By pooling expertise from various stakeholders, trials can unearth innovative solutions and achieve breakthrough outcomes that a siloed approach might miss.
For example, the synergy between Penn Medicine and Intel Corporation8 epitomises the power of collaboration. Together, they developed and used advanced machine learning techniques to study brain scans from 6,314 patients with glioblastoma (GBM), a severe type of brain tumour, collected from 71 different locations. Machine learning is like teaching computers to recognise patterns from data without specific instructions. In this project, they used a unique method called federated learning. Instead of sharing the actual patient data, sites only shared the insights or lessons (model parameters) they gained. This method allowed them to better identify different parts of the tumour with higher accuracy without compromising patient privacy.
Touted as the "single largest and most diverse dataset of glioblastoma patients in literature”, this initiative underscores the benefits of merging medical expertise with cutting-edge technology, marking a new standard in collaborative research.
I — Innovative endpoints
Traditional metrics, while valuable, might not capture the entirety of a patient's experience. Embracing innovative endpoints provides a richer, more nuanced understanding of treatment effectiveness.
For example, patient-reported outcomes (PROs) exemplify this evolution. A cancer patient might report improved energy levels or mood, which traditional metrics might overlook, but are crucial for understanding overall well-being and treatment success. Similarly, wearable devices that monitor heart rate variability can detect stress or potential cardiac issues, providing a more immediate and holistic view of a patient's health than periodic doctor visits alone.
P — Planning & proactive risk management
Clinical trials, at their core, are a blend of science, logistics, and human experiences. A holistic approach requires both a well-structured strategy and the foresight to anticipate potential challenges. By weaving meticulous planning with proactive risk management, we ensure that trials are resilient, adaptable, and patient-centric.
For example, historically, risk identification in clinical trials has not been a cross-functional process, leading to a fragmented view of risks and, consequently, poor data quality and redundancies. The introduction of Risk-Based Quality Management (RBQM) has transformed this landscape. Powered by AI and analytics, RBQM emphasises consistent data quality throughout a trial, minimising human errors and bolstering data integrity. This proactive approach integrates risk control throughout the trial's duration. With the advent of technological advancements, trials have the capability to capture and review data remotely in near real-time, benefiting participants by reducing travel and ensuring stronger compliance. Recognising the significance of RBQM, the International Council for Harmonization (ICH) made it a regulatory requirement in April 2022,9 underscoring the urgency for trial sites, sponsors, and CROs to adapt.
A — Adaptive design
The dynamic nature of medical research means that new insights can emerge even during ongoing trials. An adaptive trial design offers the flexibility to incorporate these insights, ensuring that the trial remains relevant and robust.
For instance, the use of biomarkers, specific biological indicators, exemplifies the evolution of adaptive strategies in clinical trials. Take the case of cholesterol levels, a widely recognised biomarker in cardiovascular research. In a study investigating heart disease treatments, researchers might discover that individuals within a particular cholesterol bracket respond more favourably to a specific therapy. Instead of maintaining a uniform approach, the trial can recalibrate its focus. By prioritising participants with these specific cholesterol levels, the study not only becomes more efficient, but also more relevant. This nuanced approach ensures that the research remains patient-centric, optimising the potential for breakthrough treatments that cater to individual needs, thereby enhancing the overall efficacy of heart disease interventions.
T — Training & education
The rapidly evolving landscape of clinical trials necessitates continuous learning. Ensuring that all stakeholders, from researchers to administrative staff, are abreast of the latest developments is pivotal for the trial's success.
In the dynamic realm of clinical trials, continuous learning tools and platforms have become indispensable. Online certification programs allow trial personnel to earn credentials in the latest research techniques, ensuring cutting-edge expertise. Virtual reality training sessions can offer immersive experiences in simulated trial scenarios, providing hands-on familiarity with novel procedures. Mobile learning apps tailored for clinical research can deliver bite-sized lessons on-the-go, ensuring that teams remain updated even amidst busy schedules. Additionally, webinars with industry experts can provide real-time insights, ensuring teams stay updated with emerging trends and best practices.
E — Ethical standards & data privacy
In our data-driven age, the sanctity of personal information is paramount. Clinical trials must uphold the highest ethical standards, safeguarding participant data, while ensuring transparency and trust.
In the realm of clinical trials, several measures can be taken to ensure the sanctity of patient data. Blockchain technology can be used to create tamper-proof records, while data can be anonymised to protect individual identities without hindering research. Patient portals can be developed to offer transparency, allowing participants to dictate their data sharing preferences. Incorporating third-party data audits and AI-driven monitoring can provide real-time oversight and swift responses to any discrepancies. By adopting these innovations, a holistic approach to data privacy can be achieved, fostering trust and transparency in our data-driven age.
A vision for the future
The PARTICIPATE framework is a testament to the evolving nature of clinical trials in the 21st century. With heart diseases and cancer claiming millions of lives annually, the need for effective and efficient trials has never been more pressing. This framework, with its emphasis on patient engagement, technological integration, collaboration, and ethical considerations, provides a roadmap for redefining how trials are conducted, ensuring they are patient-centric, cutting-edge, robust, and compassionate.
References:
1. How many people die and how many are born each year? Big Think, Apr 18, 2023 | https://bigthink.com/the-present/births-and-deaths-per-year/
2. Cardiovascular diseases, World Health Organization | https://www.who.int/health-topics/cardiovascular-diseases
3. Cancer Fact Sheet, World Health Organization | https://www.who.int/news-room/fact-sheets/detail/cancer
4. Global Deaths, The World Counts, Sep 18, 2023 | https://www.theworldcounts.com/populations/world/deaths
5. Wong CH, Siah KW, Lo AW. Estimation of clinical trial success rates and related parameters. Biostatistics. 2019 Apr 1;20(2):273-286. doi: 10.1093/biostatistics/kxx069. Erratum in: Biostatistics. 2019 Apr 1;20(2):366. PMID: 29394327; PMCID: PMC6409418. | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6409418/
6. Proving AI in the Clinic: An Algorithm That Accurately Evaluates Heart Failure | https://hai.stanford.edu/news/proving-ai-clinic-algorithm-accurately-evaluates-heart-failure
7. OHSU leading effort to make cancer trials more inclusive, Ohio State University, Mar 02, 2023 | https://news.ohsu.edu/2023/03/02/ohsu-leading-effort-to-make-cancer-trials-more-inclusive
8. AI Enables the Largest Brain Tumor Study To-Date, Led by Penn, Penn Medicine News, Dec 05, 2022 | https://www.pennmedicine.org/news/news-releases/2022/december/ai-enables-the-largest-brain-tumor-study
9. New strategies to manage clinical trial risk, pharmaphorum, Apr 12, 2023 | https://pharmaphorum.com/rd/new-strategies-manage-clinical-trial-risk
