Course Outline

Course Information

• The course begins at the time stated below
• The course is broken up into modules outlined below
• There will be breaks between modules

Introductory Module 1

FREE to Attend | Live & Recorded

24 September 2026 | 1:00 PM UK | 60 mins 

• AI vs. ML vs. Deep Learning: Understanding the hierarchy of intelligence and how ML identifies patterns to make predictive decisions.
• Large Language Models (LLMs) Under the Hood: A deep dive into transformer architecture (“the brain”), training on massive datasets, and next-token prediction.
• Use Cases & Managing Limitations: Addressing hallucinations, data security, and the “Faithfulness” of generated outputs

Day 1

Advanced Architectures & New Lingo

• Agentic AI: Transitioning from chat-based interactions to autonomous systems that independently plan and act to achieve goals.
• Neuro-symbolic AI & Knowledge Graphs: Combining neural pattern recognition with logical, rule-based reasoning and structured semantic networks (GraphRAG).
• API & MCP Mastery: Understanding Application Programming Interfaces (APIs) and Model Context Protocols for building custom pharmaceutical “Gems”.

Strategic Implementation & Pitching

• Framing the Solution: Learning how to design and “pitch” an AI-driven solution to leadership, moving from concept to actionable success.
• Evaluating AI Systems: Assessing existing health care AI systems to understand their strengths and weaknesses in clinical and business settings.
• The Intersection of Data & Science: Case studies on biotech leaders like Flagship Pioneering and Generate: Biomedicines.

AI in Drug Discovery & Clinical Development

• Target Identification & Validation: Rapidly analyzing genomics and proteomics to pinpoint disease-causing targets.
• Generative Biology: Using tools like AlphaFold to design novel drug molecules and predict protein structures from scratch.
• Clinical Trial 2.0: AI-driven patient recruitment, stratification, and real-time trial monitoring to reduce the “Valley of Death”.

Day 2

Forensic Due Diligence & Red Teaming

• Predictive Intelligence in DD: Moving beyond standard checklists to holistic forensic data-auditing.
• The Red Teaming Workshop: Appointing a “devil’s advocate” team to rigorously challenge asset assumptions and identify technical or regulatory “kill switches”.
• Competitive Intelligence (CI): Live demo of URL mining, SEC filing (S-1) analysis, and automated CI reporting.

Digital Medicine & Ethical Governance

• Real-World Data (RWD): Leveraging data from wearables and sensors to track behavioral patterns and digital biomarkers.
• Ethical AI: Ensuring algorithmic trust and identifying potential biases.

Moving to Action

• Scenario-Based Assignment: Designing and pitching an end-to-end AI implementation strategy for a specific pharmaceutical challenge.
• The “Watch One, Learn One, Do One” Finale: Final hands-on lab operationalizing the tools and strategies learned throughout the course.

Gareth is an experienced biopharmaceutical R&D professional, drug hunter and global project lead with 10+ years of leadership in project/program management, portfolio governance and scientific strategy. He has a successful record of progressing complex, multi-million-dollar drug development programs through internal and external initiatives. He has furthered his practical experience in both Europe and the US, in clinical, pharmaceutical, VC and academic environments facilitating the preclinical -> clinical transition of novel medicinal products. Relevant former roles and institutions include Principal Investigator/Lecturer (Harvard Medical School & Boston Children’s Hospital), Fellow and Project Lead (Vertex Pharmaceuticals), Global Project Lead (Boehringer-Ingelheim) and Asset and Scientific Evolution Lead (invoX Pharma).

In his current role(s), he leads a dynamic cross-functional global team that pushes scientific and drug development boundaries, developing novel medicinal products and drug-device combinations (modality and indication agnostic), to meet unmet patient needs worldwide. He has a wealth of experience in establishing agile governance frameworks to oversee a diverse clinical and preclinical portfolio. Notably, he has extensive experience in translational biomarker strategies, indication expansions (repurposing), and effective tech-transfer for up-scale bioprocessing of biologics.

Overseeing a global team, Gareth has a proven track record in increasing pipeline visibility and executing external collaborations. He has bridged the gap between preclinical -> clinical, implementing novel ‘first-4-patient’ initiatives, such as 5’R research frameworks, relevant clinical biomarker strategies and optimising human dose prediction models to enhance the probability of success of medicinal products.