2026 Opportunities and Challenges Facing AI in Clinical Pharmacology and Translational Research Survey

This survey aims to gather opinions on the expected potential opportunities and challenges facing artificial intelligence (AI) in clinical pharmacology and translational sciences. Your input is valuable and will help us better understand the current landscape and future possibilities in the field. The survey should take approximately 10 minutes to complete. Thank you for your participation!

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* 1. How many years of experience do you have after your terminal degree (PhD, PharmD, MD, etc.)?

 Student

 Less than 1 year

 1-5 years

 5-10 years

 More than 10 years

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* 2. How many years of experience do you have using artificial intelligence?

 None

 Less than 1 year

 1-3 years

 4-6 years

 More than 6 years

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* 3. Where do you currently work? (Please select all that apply)

 Trainee (student or post-doc)

 Pharmaceutical Industry

 Academic Institution

 Regulatory agency

Other (please specify)

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* 4. Please select the field(s) that best describe your current professional involvement. (Please select all that apply)

 Clinical Pharmacology/Pharmacometris

 Translational Sciences

 Artificial Intelligence (AI)

 Clinical Care

 Research and Development in Pharma/Biotech

 Regulatory Affairs

 Academia (specific to medical or pharmaceutical sciences)

Other (please specify)

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* 5. In the context of your current role, how do you primarily interact with or utilize AI technologies? (Please select one)

 Direct development or programming of AI algorithms

 Application of AI in research or clinical studies

 Policy making or regulatory oversight for AI technologies

 Educator or trainer in AI-related subjects

 Getting help from AI agents (such as chatGPT)

 None – I do not directly interact with AI in my role

Other (please specify)

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* 6. What best represents your current geographical location?

 Africa

 Asia

 Australia or New Zealand

 Europe

 North America

 South America

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* 7. From your perspective, what are the biggest challenges that affect the implementation of AI in clinical pharmacology or translational sciences? (Please select up to 3)

 Data privacy and security concerns

 Insufficient data quality and/or quantity

 Lack of standardized data formats

 Integration with existing systems

 Limited understanding of AI among clinical pharmacologists

 Ethical concerns (e.g., bias, fairness)

 Regulatory challenges

 Funding and resources constraints

Other (please specify)

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* 8. In your opinion, what are the biggest potential opportunities for AI in clinical pharmacology or translational sciences? (Please select up to 3)

 Automate routine tasks

 Enhanced personalized medicine and patient care

 Streamlined clinical trial design and analysis

 Optimize drug dosing and safety monitoring

 Improved collaboration between different disciplines

 Increase productivity by being helped by AI agents (such as chatGPT)

Other (please specify)

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* 9. On a scale of 1 to 5, how optimistic are you about the future of AI in clinical pharmacology or translational sciences over the medium term (next 5 to 10 years)? (1 being not optimistic at all and 5 being extremely optimistic)

1 (not optimistic at all)

5 (extremely optimistic)

Clear

i We adjusted the number you entered based on the slider’s scale.

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* 10. How important do you think interdisciplinary collaboration is for the successful implementation of AI in clinical pharmacology or translational sciences?

1 (not important at all)

5 (extremely important)

Clear

i We adjusted the number you entered based on the slider’s scale.

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* 11. In your opinion, what skills or competencies should be prioritized in education and training for professionals in clinical pharmacology or translational sciences to better utilize AI? (Please select up to 3)

 Understanding of AI algorithms and techniques

 Data management and preprocessing

 Data interpretation and visualization

 Ethical and data privacy considerations in AI application

 Collaboration and communication with AI developers

Other (please specify)

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* 12. What do you think are the most promising areas of research for AI in clinical pharmacology or translational sciences? (Please select up to 2)

 Pharmacokinetics and pharmacodynamics modeling

 Drug-drug interaction prediction

 Biomarker discovery

 Disease modeling

 Adverse event prediction and monitoring

 Clinical trial design and outcome prediction

 Drug repurposing

Other (please specify)

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* 13. How concerned are you about the potential job displacement or role changes for clinical pharmacologists or translational scientists due to AI implementation? (1 being not concerned at all and 5 being extremely concerned)

1 (not concerned at all)

5 (extremely concerned)

Clear

i We adjusted the number you entered based on the slider’s scale.

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* 14. To what extent do you believe AI should be used in clinical pharmacology or translational sciences decision-making? (1 being not at all and 5 being fully integrated)

1 (not at all)

5 (fully integrated)

Clear

i We adjusted the number you entered based on the slider’s scale.

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* 15. What barriers, if any, have you personally faced in implementing AI solutions in your clinical pharmacology or translational sciences work? (Please select all that apply)

 Technical knowledge gap

 Insufficient institutional support

 Resistance from colleagues and management

 Limited access to necessary resources (e.g., hardware, software, personnel)

 Difficulty in securing funding

 Lack of relevant case studies or best practices

Other (please specify)

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* 16. How important is public trust and understanding of AI in the successful implementation of AI in clinical pharmacology or translational sciences? (1 being not important at all and 5 being extremely important)

1 (not important at all)

5 (extremely important)

Clear

i We adjusted the number you entered based on the slider’s scale.

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* 17. Which of the following do you believe would help foster public trust and understanding AI in clinical pharmacology or translational sciences? (Please select up to 2)

 Increased transparency in AI development and decision-making

 Better communication and education initiatives for the public

 Stronger regulations and oversight of AI application in clinical pharmacology

 Inclusion of diverse perspectives in AI development

Other (please specify)

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* 18. What role do you believe professional organizations (e.g., clin pharm societies, regulatory bodies) should play in guiding the development and implementation of AI in clinical pharmacology or translational sciences? (Please select all that apply)

 Developing guidelines and best practices

 Offering AI-related education and training resources

 Advocating for AI research funding

 Collaborating with AI developers and researchers

 Encouraging interdisciplinary cooperation

 Regulating AI application in the field

Other (please specify)