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The C3 Summit: San Francisco Recap

The C3 Summit: San Francisco Recap

April 20 marked the first in our series of C3 Summits, which kicked off in San Francisco. Throughout the event, we invited industry experts to panel discussions to explore patient diversity, centricity, clinical technologies, and innovations. In this recap, we will briefly explore main takeaways from each session, focusing on challenges and insights presented throughout the discussions.

Session 1: Remote Study Team Engagement – New Approaches to eLearning Content and Training

Decentralized trials (DCTs) are a patient-centric solution that leverages remote digital technologies to enable patients to participate in trials outside of a traditional clinic. DCTs reduce overhead and operating expenses while allowing patients to collect their samples locally or from an approved facility. Since the pandemic, researchers have had to think outside the box to engage both study teams and patients to keep clinical trials running remotely, from rickshaws delivering blood samples to vetting clinical research organizations (CROs) on Zoom. Relying on CROs in remote locations for regulatory support, hunting down phone numbers, and piecing together technology to deliver massive files required a sense of previously untapped resourcefulness.

Navigating international trials and communication barriers in countries where there are no contacts or points of reference can also be a significant challenge. Furthermore, DCTs may not be suitable for every trial, and researchers need to carefully consider the trial design and technology used to ensure a study's success. For example, some patients may not be comfortable with inviting study staff into their homes, especially when they may see a different person at each visit. 

Hiring for remote trials has become more common and less complex in well-developed countries. Hiring people in overseas locations is more complicated, requiring pre-existing relationships, secure communication platforms, and encryption technologies to protect against data breaches. Recruitment for diversity can be supported by leveraging these relationships and partnering with other departments to develop a plan and start recruitment earlier than required.

Furthermore, developing an inclusive clinical trial recruitment strategy for rare diseases versus more common conditions requires different approaches. Patient advocacy groups can play a crucial role in the recruitment process for rare diseases, reducing the complexity of reaching these groups through more suitable outreach strategies. For more common conditions, it is important to ensure diversity in the participant pool by tailoring recruitment campaigns to reach underrepresented communities and partnering with community organizations. Overall, remote clinical trials have a bright future, but it requires addressing various challenges, including patient recruitment and retention, data privacy, and regulatory compliance, to ensure success.

Session 2: Patient Recruitment and Inclusivity – Engagement Strategies for Diversity and Accessibility

Recent efforts to increase access and include historically underrepresented individuals in clinical trials adds another layer of complexity to patient recruitment. In an industry where speed is always a top priority, there is a gap for more thoughtful consideration to determine how to best incorporate diversity, equity, and inclusion into our programs.

Planning for DE&I must occur early, ideally with a cross-functional team and a life cycle leader who can stick with the compound throughout the entire development process. Planning must occur prior to protocol development; otherwise, the study population may differ from those who will ultimately take the drug. Consideration should also be given in Phase 1 to ensure the profile is similar to later phases. This poses a challenge, as the financial incentive of Phase 1 studies can sometimes be a full-time income opportunity for individuals. 

Failing to consider DE&I  is detrimental as evidenced by the $834 million judgment in the State of Hawaii against BMS and Sanofi for failing to disclose the ineffectiveness of Plavix for Asian and Pacific Island populations.

The presence of comorbidities, such as BMI, presents additional challenges, which can be compounded in certain populations. Overly restrictive BMI requirements exclude otherwise eligible participants and fail to consider the public health inequities that affect these groups. Failing to mitigate these differences during development could potentially set up a product for failure post-launch.   

To reach DE&I objectives, we need to enlist the support of community physicians. Partnering research-naïve clinicians with experienced personnel creates deep infrastructure within those practices and helps close the education and clinical research literacy gaps in previously underserved communities. 

In the instance of rare diseases, patients may not be able to access care or receive an accurate diagnosis due to necessary pre-authorizations and red tape. If they can locate a practice, it can be difficult to find a physician to trust.

For rare diseases, study teams may partner with patient advocacy groups or access patient registries to identify suitable individuals.

Approaching clinical trials from a human perspective as opposed to over-engineering the recruitment process is also crucial. This involves understanding patient concerns by engaging communities and notable figures within those communities as additional advocates. Sponsors and CROs need to actively work toward immediate impact and solutions by starting conversations early, collaborating with community leaders, and creating strategies to overcome barriers to participation. Diversity, equity, and inclusion must not be just an afterthought but integrated into the entire clinical trial process.

Session 3: Real-World Examples of AI/ML Automated Risk Reduction – Patient Safety, Regulatory Submissions, and Clinical Document Quality

The use of AI in the pharmaceutical industry has revolutionized drug development, resulting in significant cost savings and improved patient care. Clinical trial data can be analyzed using AI, allowing for the personalization of drug efficacy and streamlining the drug approval process. Major pharmaceutical companies have already reduced costs by 70% and increased efficacy by 40% using AI in clinical trials. Wearable devices can also be used in conjunction with AI to improve drug development designs and find new indications for existing drugs.

Additionally, AI-powered chatbots are being used in patient support, providing personalized recommendations and answering queries quickly, saving time and resources for medical information groups. AI is also being used to automate the processing of medical documents, resulting in significant cost savings and improving accuracy. AI-powered diagnostic tools, such as those used for analyzing CT scans and X-rays, can help doctors interpret test results more accurately and quickly, leading to improved patient care and reduced workloads for medical professionals.

As AI tools continue to evolve, they will become more sophisticated and have even broader applications. Voice and content generation tools catering to more than 30 languages are expected to be used by several industries, including pharma. However, regulations will also be needed to manage the use of AI, particularly in areas such as compliance and privacy. Currently, there are no regulations governing the access, export, and sharing of data generated by AI/ML models. The emergence of GPT models presents a great area of opportunity, but their evolution and ability to support regulatory concerns need to be watched.

Additionally, as the clinical research industry demands reproducibility, there may be pushback when AI tools make recommendations based on proprietary technology. Transparency and visibility are crucial, and it's important to understand the natural built-in biases and leanings of these algorithms. This is the same foundation for bias that leads to a lack of patient diversity or population inclusion. For instance, a proposed trial that used clinical proteomics and clinical gene expression review to cherry-pick patients for a cancer therapeutic trial based on perfect response to the drug raised red flags. Having humans in the workflow to conduct quality monitoring and ensure the algorithm serves its purpose is crucial for clinical trials and beyond.

Session 4: 2023 and Beyond – Sticky Innovations and Approaches from Recent Years That Are Here to Stay (and Predictions for What Comes Next)

The COVID-19 pandemic sparked a revolution in the way clinical trials are conducted. With social distancing and remote work settling as standard practice on a global scale, medical startups and CROs have had to adapt quickly to ensure that trials continue to move forward. Fortunately, this also highlighted the potential of technology in clinical trials, both remote and onsite, and this is expected to continue as we move into a post-pandemic world.

One of the most significant innovations during the pandemic has been the increased use of electronic trial master files (eTMFs), which have helped to centralize and streamline trial data. By using eTMFs, researchers can collect and store data electronically, eliminating the need for physical copies of documents. In addition to saving time and money, this also mitigates the risk of errors and simplifies remote team collaboration. Similarly, the use of electronic patient-reported outcomes (ePRO) and electronic clinical outcome assessments (eCOA) has enabled researchers to collect data from patients without requiring site visits.

Finally, the question of patient centricity has been emphasized in recent years, particularly regarding clinical trials. With travel restrictions and safety concerns, it has been more complex to effectively recruit patients for studies. However, startups and CROs continue to identify innovative ways to ensure patient safety—for example, video conferencing, home health care, mobile lab technicians, and vans to obtain blood samples . Additionally, they have collaborated with hospitals and rehab centers to set up weekly visits for elderly populations participating in trials. These innovations demonstrate a commitment to accommodating the needs of patients and ensuring their safety and well-being throughout study involvement.


The C3 Summit focuses on relevant topics in the clinical space, including patient recruitment and leveraging AI in clinical technologies. Upcoming sessions include a focus on EU CTR, patient diversity, and eCOA. Interested in attending upcoming C3 Summit sessions in a city near you? Register today for our upcoming Boston, London or Princeton events to secure your spot to access exclusive expert insights and connect with industry peers.