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Keeping Up with the Regulatory Expectations

The eClinical Forum Risk Based Monitoring Taskforce offers some best practices for ensuring clinical data quality.

Risk-Based Approaches

Video interview with Sepehr Shojaei, VP, Design Solutions, Lightship

Lightship's Approach to Accessible, Representative, and Impactful Clinical Trials

Lightship prioritizes patient accessibility and centricity in clinical trials, ensuring a seamless and positive experience for every participant. Learn more about:

Lightship's mission and core purpose as a company

How Lightship’s mobile nursing teams and home visits enhance study participation and retention

The role of mobile research units in the community and how they enhance participant education, accessibility, and convenience

Sepehr Shojaei, VP of Design Solutions at Lightship, talks about how the company works with pharma and contract research organization (CRO) partners to support clinical trials that are patient-first and accessible.

Latest Conference Coverage

Lightship’s Approach to Accessible, Representative, and Impactful Clinical Trials

Video interview with David MacMurchy, CEO of Lightship

Accelerate Inclusive Enrollment and Delivery with Lightship

Lightship focuses on patient accessibility and centricity in clinical trials, ensuring the patient experience is a positive one. Learn more about:

Lightship's impact on achieving diversity in clinical trials by engaging underrepresented patient populations

How Lightship utilizes hybrid and decentralized trial designs to reduce patient burden

The impact a patient centric model has on clinical trial participation and outcomes

David MacMurchy, Chief Executive Officer at Lightship, offers some insights into the company's mission toward improving equity and diversity in clinical trials. 

: ChatGPT usage remains limited to administrative and support work among drug developments professionals; however, a small percentage use it for more advanced tasks, such as predicting pharmacodynamics and tracking adverse events.

: We surveyed 127 drug development professionals between August and October 2023, asking respondents about how they use ChatGPT to support their work. Questions gauged usage levels for support ranging from administrative tasks, such as editing and proofing to more advanced tasks that included generating new chemical structures, identifying new drug targets and novel therapy areas, etc. The survey also asked respondents about their organization’s official stance and outlook on ChatGPT.

: The survey revealed a diverse demographic, with 63% of the respondents being White, and holding doctorate degrees (43%). About half (49%) were employed in pharmaceutical, biopharmaceutical, or contract research organization, while 31% worked in healthcare. Approximately 46% shared that they started using ChatGPT in early 2023. However, organizational attitudes varied, 52% had no formal stance, while 30% encouraged ChatGPT’s integration in the workplace. Usage varied from basic tasks like monthly outlining (39%) to advanced tasks like predicting drug efficacy monthly (less than 10%). Overall, while there's moderate AI familiarity and adoption, organizational attitudes and usage levels of ChatGPT vary widely.

: Most respondents (52%) shared that their organization did not issue a formal stance regarding whether and how ChatGPT should be used, and 81% said that they plan on using ChatGPT to support their work. Approximately 40% of respondents share that they regularly use ChatGPT to carry out supportive tasks, such as creating outlines, editing and organizing written work, and gathering articles. Less than 10% shared that they regularly used ChatGPT to support more advanced work, including generating new chemical structures, predicting pharmacodynamics, and monitoring adverse reactions.

The application of large language modeling (LLM) has exploded over the past two years, most notably with the release of ChatGPT in November 2022. ChatGPT is an LLM developed by OpenAI, an organization whose purpose is to use machine learning algorithms to create human-like responses.

This is accomplished through the processing of large sets of data to respond to user inputs, leading to improvements of its responses through repetitive feedback.

 ChatGPT has been used successfully in a wide range of industries, including education,

In the business space, ChatGPT is gaining momentum where it has the potential to streamline customer service,

 assist in market research,6 and consolidate business decisions.

In medicine, ChatGPT has passed the US medical licensing exam,

 demonstrating the biochemical knowledge equivalent to a third year medical student,

 and has been cited as having the potential to improve clinical workflow.

 However, there are still ongoing limitations to its widespread use within healthcare, stemming from medico-legal complications and harmful or irrelevant results or hallucinations.

Despite these limitations, the potential for ChatGPT’s application in drug development abounds. For example, ChatGPT can not only be used to assist in every day administrative tasks, but can also be used for predicting and explaining drug interactions; converting molecular formulations of compounds to their simplified molecular input line-entry system (SMILES) notation

 and assisting in basic searches for protein data bank files.

Furthermore, ChatGPT can be fine-tuned for even more specific purposes to support drug discovery, such as generating potential chemical structures after being trained on the dataset of drug-like molecules

 or formulating reaction arrays for chemical reactions in high throughput experimentation.

ChatGPT can also simplify the writing process, generate queries for systematic reviews, and help non-native English writers better communicate their scientific ideas.

 Among patients, ChatGPT can be used to assist patient understanding of their medication protocol, potentially improving drug adherence.

 In sum, ChatGPT seems to offer endless possibilities within different realms of drug development.

The US pharmaceutical industry is worth $567 billion in 2022

and disruptive technologies such as ChatGPT are bound to have profound effects within the industry. Understanding the current perceptions and usage of ChatGPT in such a large industry remains critical. However, most of the work currently done on the state of ChatGPT use in the pharmaceutical industry are still theoretical and largely limited to opinion pieces. To our knowledge, this is the first study to quantify the use of ChatGPT within the pharmaceutical industry.

The survey was administered among employees working in drug development in the U.S. (N=127). Survey respondents comprised representatives from at least 45 unique organizations. The survey contained questions designed to assess the integration of ChatGPT (GPT3.5 and/or GPT-4) into respondents' daily job functions and explore associated challenges and barriers. 

ChatGPT usage was assessed using a series of questions about tasks, ranging from administrative tasks such as creating outlines, spell checking, and organizing written work to more sophisticated, tailored usage, such as predicting pharmacokinetics and pharmacodynamics as well as predicting the efficacy and safety of potential drugs. The estimated completion time was approximately 15 minutes. Data collection occurred from August to October 2023. 

All methods were performed in accordance with the relevant guidelines and regulations by including a statement in the methods section to this effect. The study was reviewed by and received exemption status from the Tufts University School of Medicine Institutional Review Board.

The survey was distributed among participants from an internal, proprietary distribution list containing the emails of drug development professionals. Additionally, the survey was shared on Tufts Center for the Study of Drug Development (CSDD)’s social media platforms, specifically LinkedIn and the Tufts CSDD website.

Monetary compensation was not offered for completing the survey. However, participants were provided with the opportunity to vote for their preferred charity from a list of options, which included the American Civil Liberties Union Foundation, Southern Poverty Law Center, The Center for Constitutional, Child Foundation, and Black Mamas Matter Alliance. The charity receiving the highest number of votes was awarded a $300 donation. Respondents also had the option to receive a high-level summary of the study results by providing their email address.

A total of 127 participants completed the survey. The majority identified as White (63%), followed by Asian (21%), multi-racial (7%), Black (5%), and Latino (4%). Half, 50%, identified as men and 46% as women. The mean age was 50 years, and the average work experience was 21 years.

Educational backgrounds varied, with 43% holding a doctorate's degree, 32% a master's degree, 19% a bachelor's degree, 5% a professional degree, 1% an associate degree, and 1% having completed high school. Organizational sizes were distributed as follows: 45% from small-sized organizations, 31% from large-sized organizations, and 24% from mid-sized organizations.

Approximately 50% of respondents were currently employed in pharmaceutical/biopharmaceutical or a contract research organization; 31% of participants worked in an academic medical center, large healthcare system, private clinical trial investigative site, or community-based clinical trial investigative site; and 19% worked in consulting or were solution providers. Additional demographic information is provided in 

Most participants held positions at the manager, senior manager, or director level, comprising 46% of the respondents. Entry level employees accounted for 5% of the respondents. The remaining 49% occupied roles such as C-level executives, owners, senior individual contributors, vice presidents, senior vice presidents, and other positions.

Organizations’ Attitudes Toward ChatGPT

Approximately 52% of respondents shared that their organizations did not provide a formal stance regarding the utilization of ChatGPT. In contrast, 30% of respondents shared that their organizations actively promoted the integration of ChatGPT, while 18% discouraged or prohibited its usage.

Relatedly, when asked about the availability of ChatGPT Plus subscriptions in their workplace, most respondents, 69%, shared that their workplace currently did not provide it and had no plans to do so. When asked about risk management related to ChatGPT, 45% expressed that because they had no intention to use ChatGPT, consequently, they had no plans for risk mitigation.

On the other hand, 17% shared that their organization hired a team of AI specialists tasked with establishing parameters and internal guidelines for its use. Additionally, 10% are offering training to leverage ChatGPT capabilities, while 8% have formed partnerships with OpenAI. See 

Next, among those who said that they are using ChatGPT in their everyday work, we explored for what specific types they were ChatGPT. 

 for a detailed description of the different tasks.

The tasks were categorized into three usage levels, ranging from basic to advanced. Basic tasks included administrative activities such as creating outlines, editing, and proofing reports or manuscripts. Approximately 39% of respondents shared that they used ChatGPT to create outlines for work while 35% shared that they used it for gathering articles and organizing references.

Next, intermediary tasks included slightly more advanced activities such as data management and analysis or explaining novel or difficult concepts. About 39% of respondents shared that they use ChatGPT to help explain difficult to understand concepts; however, less than 20% of respondents shared that they use ChatGPT to handle data.

Lastly, the advanced category contained activities, such as generating new chemical structures and predicting toxic effects of new drugs. Only 14% of respondents shared that they use ChatGPT to identify new drug targets. Less than 10% of respondents shared that they use ChatGPT to assist in the more advanced tasks related to drug development, such as predicting pharmacodynamics, writing code for docking, or monitoring adverse events.

Our study provided baseline ChatGPT usage among drug development organizations to understand whether and how organizations are adopting ChatGPT into daily use. Overall, 52% of organizations represented in our survey did not provide any guidance on the utilization of ChatGPT. Most organizations in our sample—close to 70%—shared that they do not plan on formally implementing ChatGPT. Both results suggest a general hesitancy

 toward using ChatGPT across organizations.

Next, we examined individual’s usage and attitudes towards ChatGPT, which was moderately more favorable to the adoption and usage of ChatGPT. For example, close to 40% of respondents shared that they used ChatGPT to handle basic tasks, such as creating outlines, editing, and organizing written work on a regular or monthly basis. When asked about intermediary tasks, such as analysis, management, storage, and retrieval of data, less than 20% of participants shared that they used ChatGPT for these tasks on a monthly basis.

Next, when asked about more advanced tasks, such as generating new chemical structures or predicting toxic effects of drugs, less than 10% of participants shared that they use ChatGPT to support them in these tasks monthly. Most participants shared that they do not plan on using ChatGPT for more advanced tasks.

What these findings suggest is that most organizations and professionals working in drug development—whether in pharmaceutical sponsor companies or academic research centers—are hesitant about incorporating ChatGPT into their workflow. However, the percentage of those in our sample who regularly use ChatGPT to support their work was higher than the average usage rate among active users of ChatGPT in the general American population, suggesting that those working in the field of drug development may be more comfortable using ChatGPT to support their work.

The study also points to promising potential for future usage in various aspects of drug development, even for the more advanced tasks. For example, identifying new drug targets had the highest level of moderately regular usage—at least a few times a year—among the more advanced tasks.

This finding suggests that although usage of ChatGPT to support robust tasks, such as generating new chemical structures or monitoring adverse drug events, is relatively low compared to less complex tasks, such as editing or performing literature reviews, the potential to scale its usage remains. How drug development companies develop their own datasets for training or create partnerships with OpenAI remain to be seen. Once more robust features are built into ChatGPT and more studies demonstrate its efficacy,

 more drug development professionals may utilize ChatGPT to help them to streamline and perform advanced workflows.

This study has several limitations that should be considered. First, the sample size was relatively small and was only from the United States, which limited the generalizability of the findings. However, data were collected from professionals from biopharmaceutical companies, contract research organizations, and academic institutions. This wide range of industries and views provide a preliminary baseline benchmark of current and future usage of ChatGPT among professionals working in drug development.

Additionally, the study did not evaluate the impact of ChatGPT on actual work outcomes. Future studies may wish to tie different levels of ChatGPT usage to performance metrics—such as study level outcomes; individual work metrics, such as productivity, job satisfaction, and workload—to evaluate its impact on real-world outcomes. Nonetheless, before such studies can be conducted, benchmarks need to be clarified on what constitutes ChatGPT usage in drug development and how AIs will be trained on datasets (i.e. protein data bank files).

In conclusion, the study provided an overview of the baseline usage of ChatGPT among drug development professionals in the United States. While the results from our sample suggest that usage of ChatGPT to support everyday work is still in its infancy, the study also highlights the potential for increased usage of ChatGPT to assist professionals with more advanced tasks.

, Tufts Center for the Study of Drug Development (CSDD), Tufts School of Medicine, Boston, MA USA.

, McGill University, School of Medicine, Montreal, Canada.

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Jurnal Teknologi Dan Sistem Informasi Bisnis

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7. Generative AI for Business Decision-Making: A Case of ChatGPT | Management Science and Business Decisions. Published online July 1, 2023. Accessed May 15, 2024. https://publish.thescienceinsight.com/index.php/msbd/article/view/63

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9. Ghosh A, Bir A. Evaluating ChatGPT’s Ability to Solve Higher-Order Questions on the Competency-Based Medical Education Curriculum in Medical Biochemistry. 

10. Rao A, Pang M, Kim J, et al. Assessing the Utility of ChatGPT Throughout the Entire Clinical Workflow: Development and Usability Study. 

11. Dave T, Athaluri SA, Singh S. ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations. 

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13. Mahjour B, Hoffstadt J, Cernak T. Designing Chemical Reaction Arrays using phactor and ChatGPT. Published online February 28, 2023. doi:10.26434/chemrxiv-2023-2tfdv

14. Sallam M. ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. 

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15. Juhi A, Pipil N, Santra S, Mondal S, Behera JK, Mondal H. The Capability of ChatGPT in Predicting and Explaining Common Drug-Drug Interactions. 

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17. Gelles-Watnick EP and R. Most Americans haven’t used ChatGPT; few think it will have a major impact on their job. Pew Research Center. Published August 28, 2023. Accessed May 15, 2024. https://www.pewresearch.org/short-reads/2023/08/28/most-americans-havent-used-chatgpt-few-think-it-will-have-a-major-impact-on-their-job/

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Despite limitations to its widespread use within healthcare, there is great potential for ChatGPT’s application in drug development.

Mapping Baseline ChatGPT Usage to Support Drug Development

Clinical research is more complicated and expensive than ever. That means the journey from a medical hypothesis to a widely available treatment requires cooperation from numerous financial, regulatory, and research organizations. The closest working relationships within that ecosystem are between pharmaceutical, biotech, and medical device sponsors, contract research organizations (CROs), and clinical research sites.

These relationships over the years have struggled. To make transformative improvements in clinical trials, the entire industry needs to reimagine clinical research and collaborate in new ways to enter a new era of conducting clinical trials. Indeed, while clinical research in the last half-century has undergone countless advancements in the pursuit of safer, faster, and more effective drug, vaccine, and device development, many processes that require collaboration across sites, sponsors, and CROs feel painfully slow, redundant, and disconnected.

Despite sponsors and CROs having the best intentions, sites generally still experience the processes handed to them as “how things have always been done.” For all the intentionality of making improvements, there are still gaps. Sites still trudge through the same old processes, but now with added redundancy and burden as more and more technologies are imposed upon them from sponsors. In fact, according to a 2023 Study Activation 

, 56% of sites cite technology as the biggest burden among all study startup activities.

“One issue that plagues sites is the lack of a universal process across all sponsors,” explained Rosalie Filling, vice president, senior global head R&D operations at Endo. “Sponsor A wants things done their way, Sponsor B wants to do it this way, Sponsor C wants to use this system…sites are left learning, managing, and juggling all of these different paths, which often impacts their ability to focus on the patients and trial execution.”

Together, the clinical research ‘village’ can solve the problems plaguing us. Here, sites, sponsors, and CROs discuss three top clinical trial pain points and potential remedies.

the burden of feasibility surveys has increased over the past five years. The feasibility process, where redundant questions and cumbersome processes create inefficiency, is universally dreaded by sites and sponsors alike.

“We take on hundreds of studies a year,” said Denise Snyder, associate dean for clinical research for Duke University School of Medicine. “We want to avoid repeating the intake process every time we consider a new study.”

“You should have the table stakes figured out,” echoed Nick Spittal, chief operations officer from Velocity Clinical Research, the largest global organization of fully owned clinical research sites. “Feasibility can be boiled down to basically two questions: 'Do I have access to the appropriate study subjects at my site?' And 'How many of them can I enroll in the planned time frame?' Everything else, like ‘I don’t have ACME centrifuge model XN84,’ can be figured out later.”

Rather than the current practice of reaching out directly to the principal investigator and asking redundant or non-study-specific questions in site feasibility questionnaires, sponsors and CROs should reach out to a central office for their sites. It would also be helpful to pull previous site and/or PI data already on file rather than asking the site to start from scratch; instead, they could verify the information.

For their part, sites can help by creating a resource or one-pager that directs sponsors to their central research office and respond to feasibility questionnaires with that document. Sites can also create email distribution lists for departments such as regulatory, contracts and budgets, and business development (for trial leads and feasibility questionnaires) to both make the process easier on sponsors and CROs and ensure a site doesn’t lose work or progress when an employee goes on vacation or departs the organization.

Technology can streamline the entire feasibility process. In a single system, sponsors can send feasibility surveys to sites to complete, and if sites have completed it before, they simply need to confirm or update their information. When sites and sponsors collaborate in the same system, they streamline communication and get instant visibility into the process.

Pain point 2: Site qualification visits/site initiation visits

Site qualification visits (SQVs) have tremendous opportunities to be streamlined. Qualification should be a relatively static, non-protocol-specific assessment that occurs only periodically. Sites could have platforms that sponsors could access with administrative information about facilities and their capabilities. In-person reviews could happen less frequently, perhaps annually. With both those components in place, SQVs could be waived—as is already done when a site and CRO/sponsor have a preferred partnership. Lastly, sponsors could use CT.gov to collect resumes, licenses, and other information about sites.

“Sites often view SQVs as sunk costs because they are pulling staff away from patients,” explained Nick Palumbo, director of feasibility and enrollment forecasting at Takeda. “We are trying to aggregate various data sets and metrics to take this visit off the critical path. For instance, we look at historical relationships, performance metrics, and feasibility questionnaire responses plus other insights and then may pre-qualify the site before a visit. Some sites are also requesting the pre-study meeting to be virtual, where possible.”

Similarly, the site initiation visit (SIV)is also worth revisiting. This critical meeting occurs before a site begins enrolling patients to ensure that they are fully prepared to conduct the study according to the protocol, regulatory requirements, and Good Clinical Practice (GCP) guidelines. Fundamentally, SIVs are about teaching the clinical site how to successfully enroll patients and ensure that the process follows the protocol in a quality manner. But too often, they try to accomplish too much at once.

Ideally, the focus of the SIV should be on practical, immediate tasks and questions that may arise during the first few visits, rather than preparing for far-off future events (e.g., closing the trial). SIVs should provide everyday advice, such as what to do if unexpected clinical results occur and who to contact for immediate assistance. Some parts of the SIV, such as verifying temperature logs for freezers, could also be streamlined by sending logs via email or a shared cloud-based platform rather than physical inspection. Sponsors could also consider providing long-term training modules to alleviate the need for lengthy SIVs.

Rather than using PowerPoint decks or antiquated systems, sponsors can increase collaboration by providing an engaging learning management system where site teams are properly trained on the trial. This ensures compliance and reduces protocol deviation, giving sponsors the confidence that their sites have what they need to conduct the trial.

Contracts and budgets continue to be a thorn in the side of sites, sponsors, and CROs alike. Contract and budget (C&B) negotiations significantly delay site activation, often taking eight weeks—even longer for some institutions. A major challenge arises from the lack of transparency in the C&B process, as sponsors often do not allow CROs to access previous agreements, even when there is an existing relationship between the sponsor and the site. Additionally, while sites are asked to justify their charges, they do not usually receive justification in return. This is especially true in the US in Medicare Coverage Analyses (MCAs). Without justification, C&B negotiations take longer and, where an MCA is needed, the site must start from scratch with their own analysis, which can add weeks to the process.

“We hate being stuck in the back-and-forth, inefficient rework cycles involving contracts, budgets, and amendments,” added Mark King, vice president of research and innovation at Novant Health, an integrated network of more than 850 healthcare sites, including 19 hospitals. “Sponsors/CROs must recognize that mid to large-sized trial sites are working with many sponsors simultaneously. We have dozens of studies in start-up at the same time. Those who can supply final documents early and respond to questions quickly are going to have their trials opened more efficiently. When there are outstanding documents, drafts, or amendments in play, studies may be de-prioritized by sites, significantly impacting timelines.”

Takeda’s Palumbo added, “We know this is a major pain point, so we try to establish master clinical trial agreements (CTAs) with preferred sites using agreed-upon standard language, but it is still difficult. To help expedite timelines and gain accountability, we have taken a lot of that negotiation work in-house. The larger academic centers have a lot of administrative red tape, especially in oncology, and it tends to slow site activation.”

First, learning from successful sponsor-site and CRO-site preferred partner programs can provide valuable insights into optimizing contract and budget management in clinical trials. Sponsors and CROs can make better use of existing contract and budget terms to reduce negotiation times and associated burdens on sites. Pre-negotiated contracts and budgets should cover non-protocol-specific items such as CTAs, confidential disclosure agreements (CDAs), and consent language. Additionally, budgets for common procedures like ECGs, infusions, and consent should be pre-negotiated and updated annually. Exploring the use of artificial intelligence to extract language for a master contract template could further streamline the process.

There is also a pressing need for enhanced communication between sponsors, CROs, and sites throughout the C&B process. Ensuring that outstanding documents, drafts, and amendments are addressed promptly will reduce site activation delays. Stakeholders might consider adopting a dedicated platform for C&B document exchange and version control. And using integrated technology solutions that connect site-owned systems with sponsor-provided platforms can also minimize duplicate work and streamline document management.

It takes a village to raise a trial, but most stakeholders are siloed on isolated islands. 

Ioannis Karageorgos

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