Technology

Developing a medical AI model is defining the parameters of the problem that needs to be solved.

Avak Kahvejian, PhD, a general partner with biotech incubator Flagship Pioneering, discusses how AI is rearchitecting methods—and mindsets—in drug discovery and development.

Merck’s executive director, operations lead, global medical affairs and outcomes research discusses how data is helping to identify scientific leaders.

The key steps for pharma in pivoting from proof-of-concept experimenting to enterprise-scale value.

With healthcare at a key crossroads of policy, technology, and science, Sanofi CEO Paul Hudson shares the Big Pharma’s formula for navigating the new age of innovation, where running from risk is not an option.

As drugmakers navigate an increasingly complex terrain of scientific and digital influence, the ability to accurately identify and understand both key and digital opinion leaders is vital for effective engagement.

A Harvard Business School Healthcare Alumni Q&A with Professor Eric Mazur of Harvard University.

Powering learnings of the dark genome to tackle disease at its source.

Pushing for access wins in quickly evolving market and digital health landscapes.

Ex-Wall Street trader is helping reshape how patients receive biologics.

Pioneer of cell-reset technology steers science-to-startup transformation.

The AeroRx Therapeutics CEO discusses new treatments and how the industry at large is reacting to them.

The Google Cloud director discusses AI implementation and workflow.

Strategies for biopharma in integrating agentic AI—to achieve incremental gains in efficiency, while delivering meaningful progress in how data insights inform commercial decision-making.

Bridging the last mile to clinical actionability.

With AI expected to play a significant role in drug approvals, how can companies build data sets that are ready for AI?

Gene Mack, CEO, Gain Therapeutics, explains how the company’s Magellan AI platform analyzes novel protein binding sites to identify and design drug candidates beyond what’s currently available in the public domain.

By using real-world data (RWD) and the insights derived from it, real-world evidence (RWE) earlier in research and development, drugmakers can make more informed decisions and reduce the financial risks that drive up drug prices.

Computational chemistry combined with AI technologies has become a powerful tool for assessing small molecule properties, high-resolution protein structures, and molecular mechanism of action, as well as optimizing target selection and small molecule design.

Organizations commonly navigate outdated systems that make collaboration harder and breakthroughs slower, causing delays, missed insights, and costly rework.

Webinar Date/Time: Thu, Aug 14, 2025 3:30 PM EDT

Despite surging GenAI adoption in pharma and the FDA’s recent embrace of the technology, a trust gap remains with GenAI implementations. The story describes four essentials that improve trust in GenAI so that pharma and biotech teams can better navigate the present time of uncertainty.

A global survey of scientists and informaticians reveals growing AI investment across the biopharma value chain, but highlights gaps in data integration, standardization, and infrastructure that threaten to stall progress.

With reports that FDA’s AI Elsa is “confidently hallucinating” studies that don’t exist, the use of AI to streamline drug review and speed up approval is not here yet.

The EVERSANA team discusses its new technology center that has a goal of pharmatizing AI.