Slalom Point of View: Clinical Trials in 2021+: The future of clinical trials is accelerating thanks to a pandemic’s worth of attention
The COVID-19 pandemic has caused untold suffering across the globe, which forced our global community to rip up the rule books, break apart norms, and change the way we live forever. No industry has felt this momentous change more than the life sciences industry.
Not all change has been detrimental to industry and humanity’s quest for better health outcomes. Quite the opposite. Several positive changes will help shape our new health journey future:
- Digital transformation - to the chagrin of fancy executive PPT strategies trying to push change unsuccessfully for years - has accelerated dramatically as lockdowns required the healthcare workforce to adopt and adapt to new tools.
- Personalized and digitally supported therapies that may be diagnosed, administered, managed, and monitored remotely without the need for in-person HCP visits are now critical to ensure health systems load balancing, continued journeys toward health maintenance, and adherence.
- Finally: A greater awareness and need for faster, more-efficient clinical trials resulted in the fastest vaccine development and deployment in history. The speed, safety profile, and efficacy of not 1, but 3 successful vaccines in under 1 year baffled even noted infectious disease experts.
The Health Industry’s Clinical Trial Transformation
Life Sciences, healthcare organizations, clinical research organizations, and many other health related bodies have come together to collaborate in an unprecedented manner. Operation Warp Speed and the rapid development of Covid-19 vaccines set a high bar for R&D timeline expectations. These expectations will only compound for at-risk or diseased patient population groups eager for a cure. Clearly, drug development timelines are fungible with the appropriate focus and support.
Even in January 2020, it was largely accepted as a necessary if not required fact that drug development would take 10–15 years. The pressure on pharma organizations, both internally and externally, will be to start-up, run, and complete clinical trials faster. As a result, we will see an innovation explosion across all stages of the clinical trial process that will impact organizational structures, processes, technology, and patient expectations.
Accelerating Study Start-Up
Timeline reduction during the start-up phase is critical to shortening time-to-approval via reduced trial durations. Organizations will seek to reduce redundant activities by streamlining processes, becoming data-literate, and collaborating.
Already, organizations are seeking to digitize the traditionally labor-intensive protocol design process. Once digitization is made possible, study design data becomes liquid and will no longer be locked away in analogue, unusable study formats. Advanced AI may one day design protocols to achieve desired study endpoints by not only learning from previous successes and failures, but also with real-time patient population data, site burdens, molecule success probabilities, and life science company organizational capacity.
Patients, supposedly at the center of the life science industry, have historically been left out of protocol design. Protocols created without patient input only find errors and patient hardships once study recruitment is in progress — these errors may delay studies and put undue burden on patients. Slowly, this is changing where patient representatives or organizations are better collaborating with life science companies which has brought new ideas, perspectives, and recruitment networks to clinical studies.
Faster, more targeted, and site-complete patient recruitment is needed (37% of all sites under-enroll) The use of predictive technologies in demographic populations and a trusted data collaboration between health systems, governments, health authorities and life sciences companies will allow for more efficient and less burdensome trials across the industry.
New trials are catalysts to massive domino effects of disruption. New trials mean new teams. New teams mean new ways of working together. New sites mean working with new site teams. New vendors need to be on boarded, new technologies introduced, new patients recruited, new molecules developed. Modern, patient-centric, and cross-organizational operating models — supported by effective use of data and technology — will speed timely processes. Using umbrella or basket trials can make better use of existing infrastructure, start-up, and team dynamics. Reducing the time between phases by utilizing AI or other machine learning techniques will result in a much faster speed to market for promising molecules. We will see far more post-marketing surveillance using remote technology to better aid in extremely targeted follow-up indications and safety data furthering efficient use of funds, data, time and investigator, government, and patient expectations.
Trial Diversity and Equal Representation
Clinical trials are proxies for real life and when the proxy no longer represents real life, it loses relevance. There is increasing pressure and awareness that clinical trials need to reach more representative patient populations. Around 75% of clinical trials participants are white, yet over 40% of the (US) population are non-white. Not to mention that rare and specialty diseases in many countries impact non-white populations disproportionately. Life sciences companies must intentionally ensure inclusive, diverse, and equitable (IDE) access and representation to trials.
Better awareness and education across a broad spectrum of socio-economic demographics is needed to break-down unapproachable scientific terminology. Funding for basic science and scientific method education has decreased in our underserved and public education populations compounding the learning curve at adulthood.
Democratization of and public access to clinical trial data remains a barrier to entry. Not only are the websites buried in (or hidden from) highly trafficked digital channels, but they have poor experience design, lack consolidated views, are difficult to search, are not accessible for certain disabilities, and contain convoluted terms. Modern and more accessible technology — via a global consortium or global, coordinated governmental effort — is needed to even meet the minimum standards we expect.
Finally, trust is the backbone to achieving fully inclusive, diverse, and equitable trials. Governments and corporations have exploited disadvantaged groups for centuries — and even continue to do so today such as the legacy of Henrietta Lacks. Trust being built over time, never earned easily, and destroyed instantaneously will require years of doing the right thing across the entire health industry.
Patient Recruitment
Building off the need for IDE trials, patient recruitment remains a challenge in general. Not only is it difficult to find and convince patients to join a trial, but increased competition across the life sciences industry has patients choosing between trials and life science companies fighting over the same patients. The capitalistic tendencies create perverse incentives which end up harming the overall patient population more so than a utilitarian view towards health.
Utilizing new access points and expanding the use of independent sites will help remove some barriers for patient participation. Independent sites are faster and closer to patient communities but are typically underfunded and in need of technology enablement. Identifying diverse geographic areas for those sites will be critical. Democratizing sites across life science industry companies — versus several exclusive site contracts — is needed to ensure the most benefit for patients versus the most benefit for corporations. Supportive, but democratic regulation and collaborations are needed.
“Cutting back on in-person visits could make recruiting patients easier and reduce dropout rates, leading to quicker, cheaper clinical trials,” said Dr. Ray Dorsey, a neurologist at the University of Rochester who conducted remote research for years.
Clinical trials recruitment teams need to innovate around how they find, engage, and educate patients. Utilizing different channels, such as social channels (TikTok, Instagram, Spotify), search engines (Google, Bing), and targeted messaging platforms can reach previously unreached communities of people. By humanizing communications in outreach (the average reading age is 12 years old) and avoiding technical / medical jargon will also help. Human-centric research techniques will help to gain a deeper understanding the reasons for non-participation (cultural, economic). By using more advanced analytical technologies to compress the screening process, it will not only help to speed up the recruitment process but also identify critical diverse segments and target populations for clinical success.
Transformational Technology
Better technology adoption but, more importantly, the capability for using technology in an agile manner will transform trial speed and effectiveness. An adaptive technology stack — supported by democratized data — will help guide and in some cases save trials from failure.
The pandemic changed how trials are run out of necessity — twice as many CTs as normal were stopped due to the pandemic — which drove the innovations and continued focus on technology supported trial protocols. Some trial teams quickly adapted such as one team which changed the patient requirement from driving 3 hours to a lab to drop off and review samples to dropping off blood locally and reviewing over video call.
Technology connections across the end-to-end trial timeline and parties will support parallel trial analysis, supportive patient health management (such as mental health burdens like difficulties finding a ride to the clinic and their effects on physical trial outcomes), and effective communications.
An adaptive technology stack will enable virtual trials. Imagine a data-only trial performed digitally and ad hoc to find new indications or safety profiles. Patients may find themselves with new treatments immediately available and our health system won’t need to fund superfluous or hypothesized trial outcomes.
Better data capture and technology is needed across the trial spectrum to make this a reality, but it must also be coupled with regulatory support. More trials will incorporate remote monitoring and utilize advanced CTMS and eCOA. This will increase the need for more two-way communication between patients and trial investigators with more emphasis placed on the patient experience. By 2021, 40% of the top 100 life sciences companies will begin to implement digital trial pilot programs. Virtual clinical trials will place more pressure on organizations to adapt to new ways of working, to leverage new technologies and to deal with a proliferation of data and data sources. New governance structure will need to be established being supported by technology.
Proven increased evidence of the effectiveness of digital therapeutics will see an increase of their use in clinical trials leading to an increased need for better and faster technology. As organizations understand and identify digital biomarkers, there will be an explosion of research into the topic. Already, the FDA has approved the first game-based digital therapeutic to improve attention function in children with ADHD. No pharmaceutical or molecule is needed for therapy as behavioral and neuroscience research and modern technology is better able to treat patients with long-term success.
Not More, But Better Data
A consistent theme throughout clinical trial effectiveness and efficiency is data. Organizations in the clinical trial ecosystem have already invested into their data and analytical capabilities, but more is needed.
Effective and accessible data pipelines are not only difficult to build, but require constant investment to ensure interoperability between organizations, reusability, secure access, and reliability. Those organizations that have the luxury to pour significant investment into their master data, ingestion processes, data analysis, processing, machine learning / AI, external data set integration, and more will be the organizations that will gain a significant competitive advantage. Failure to do so will inevitably lead to dwindling pipelines and, ultimately, redundancy. Legacy, disconnected systems impact the entire clinical value chain from patients who want their data, to investigators burdensomely sifting through hundreds of separate data files, to life science companies hoping to extract move value and therapies. Compounding investment need is the lack of technical and data savvy clinical executives. Strong leadership with a focused and cascaded vision for technical perfection must be paired with the traditional need for clinical literacy.
Collaborative data sharing agreements are critical to decentralized and utilitarian progress for the market forces to uncover the best treatment options available. Already, several health organizations have data sharing - direct access, third-party for-profit companies (e.g., Flatiron), data purchase - agreements in place to support data-driven insights. Targeted regulation to publicize clinical information so it may be accessed outside golden walls will help more nimble upstarts find new therapies or indications.
Any cornerstone to data-driven change is security and trust. Health data is the most sensitive information for the vast majority. Malicious actors have an easy path to profit given the sensitivity. In cybersecurity, the defense is always behind and underappreciated — it’s not until a breach occurs is the proper attention given to data security and, usually, it’s only for a brief point in time after the attack.
Finally, a concept of patient-owned-and-operated data is emerging to better allow for individuals to opt-in or out of broad or targeted trial support. A growing demand from patients (“Give Me My Damn Data”) who want more access to their own data could have fundamental implications the way trial data is collected, stored and shared . Technology to make this possible has emerged from the recent digital advertising regulations. Blockchain and similar technologies may make it even easier to ensure secure, traceable, and compliant data ownership, sharing, and democratization.
Slalom is uniquely positioned to best support these future trends through our in-depth knowledge of the ecosystem coupled with our leading technology expertise.
Meet the Authors:
John Pugh is a director in Slalom’s Life Science practice in London. He’s spent 18 years in Life Sciences innovating, challenging and driving a more digital mindset.
Collin Burdick is a Life Sciences consulting leader at Slalom in San Francisco, an award-winning digital leader, and an accomplished operator with a passion for delivering transformational initiatives and building strategic delivery teams in support of better patient outcomes.
Slalom is a modern consulting firm focused on strategy, technology and business transformation. Our healthcare and life sciences industry teams partner with healthcare, biotech and pharmaceutical leaders to strengthen their organizations, improve their systems, and help with some of their most strategic business challenges. Find out more about our people, our company and what we do.
