3 SundAi Brunch with Shazad Jafri скачать в хорошем качестве

3 SundAi Brunch with Shazad Jafri

Welcome to SundAi Brunch with Dr Kish & Guests A weekly podcast exploring the intersection of healthcare, AI, media, and ethical communication. Where medicine meets media. Where communication becomes care. This week I am joined by Shazad Jafri. Here's a summary of our discussion on medical affairs, AI, and governance. We discuss Shazad’s journey from clinical pharmacy into medical affairs and pharmaceutical code compliance. Over the past decade, he’s worked across small, medium, and large pharma, now operating independently as a medical signatory and governance specialist, helping smaller organisations build consistent, robust decision systems. Shazad is actively learning how AI can responsibly support business processes, especially in medical affairs, with a firm emphasis on never compromising patient safety or scientific integrity. He stresses transparency about being in a learning phase because the field moves too fast for definitive “experts.” A clear explanation of medical affairs frames it as patient-safety-centred work spanning medical information (answering clinician/public queries), identifying scientific gaps, and pharmacovigilance/drug safety. The hosts emphasise that in life sciences, everything publicly released must be rigorously checked, referenced, and substantiated. Contrasting organisational scales: large pharma has deeper expertise and controls but more stakeholders and governance steps, making processes slower; smaller organisations enable quicker test-and-learn cycles but require equal discipline in compliance and accountability. The core implementation principle: start with safe use cases, define boundaries, and keep humans in the loop. Three priority AI opportunities in medical affairs: 1) Knowledge management: faster access to evidence, precedents, and internal guidance. 2) Communication support: drafting clearer versions of complex materials for internal review, always verified by experts. 3) Quality systems: pattern-spotting in issues to reduce repeat mistakes and enable continuous learning. For piloting AI in large organisations, Shazad advises early stakeholder alignment (legal, digital/IT, medical, governance) around patient value, clear outcome measures, and transparent sharing of pilot learnings to avoid siloed efforts. On content creation, Shazad produced a short, non-promotional explainer video about the ABPI Code to address knowledge gaps among those curious about pharma (including NHS clinicians). He received positive feedback and learned from stylistic critiques (e.g., voice choice), aiming to create more content—with the host encouraging him to use his own voice. Regarding clinicians using tools like ChatGPT for patient notes, Shazad’s immediate concerns are privacy, data security, and clinical safety. While summarisation can appear low-risk, tool choice and environment are critical. He notes the risk of hallucinations and the persuasive style of outputs, advocating a hybrid approach: approved, tested tools; clear policies; robust double-checking; and maintained clinical accountability. On shadow AI (use of non-approved tools with sensitive data), he warns it’s a real issue driven by unmet demand and accessibility. The solution is not blame but providing safe, approved alternatives, training on boundaries, and setting clear accountability and auditability. To stay grounded amidst rapid change, Shazad focuses his learning on his core domains—content approval, ABPI governance, and medical affairs processes—testing ideas against constraints like auditability and compliance, and developing judgment in areas such as limitations, bias, and responsible prompt structuring. His definition of patient-centred innovation: optimistic but careful, with unwavering accountability. In medicines, AI can assist, but responsibility cannot be delegated; protecting patients and evidence-based practice remain paramount. I hope you enjoy our conversation over SundAi Brunch. Date of content creation: 2026-02-15.