In this GEN interview, Nobel Laureate David Baker, PhD, emphasizes that designing proteins from scratch is reality and unpacks what's needed for AI to transform medicine.

Artificial intelligence (AI) and machine learning partnered with big data generation at unprecedented scale is transforming the worlds of biotechnology and pharma, particularly in the arena of drug discovery. From generative AI to unlock novel drug candidates to virtual cells that gleam insights across multimodal biology, we are witnessing the cusp of an exponential curve of AI innovation that is poised to enhance and perhaps overhaul the design and validation of novel therapeutics. In 2024, GEN debuted our virtual summit, The State of AI in Drug Discovery, which drew a record audience. This year’s summit provides a platform for an outstanding group of researchers, evangelists and entrepreneurs to showcase the latest advances, applications and challenges regarding the deployment of AI across therapeutic development. The program features many of the most exciting companies and organizations powering the AI revolution, including NVIDIA, Xaira Therapeutics, Recursion, Chan Zuckerberg Initiative, Arc Institute, Generate: Biomedicines, and more! Please join us on October 29th for a dynamic program featuring: A featured presentation with Bo Wang, PhD (Xaira Therapeutics) on the promise of multimodal AI for health care The democratization of small molecule drug discovery with the developers of Boltz-2, Gabriele Corso, PhD (MIT), Regina Barzilay, PhD (MIT), and Najat Khan, PhD (Recursion) Evolving industry trends across the AI therapeutic landscape with Derek Lowe, PhD (Novartis and author of "In the Pipeline"), Molly Gibson, PhD, (Flagship Pioneering), and Stacie Calad-Thomson, PhD (NVIDIA) Building the virtual cell with Theofanis Karaletsos (Chan Zuckerberg Initiative), Emma Lundberg, PhD (Stanford), Hani Goodarzi, PhD (Arc Institute), and Ron Alfa, MD, PhD (Noetik) What’s next for AI in protein design with Surge Biswas, PhD (Nabla Bio), Tharindi Hapuarachchi, PhD (Generate: Biomedicines), and Oliver Vince, PhD (Basecamp Research) Breakout sessions from our event sponsors, Revvity Signals, Benchling, and Telesis Bio. Registration for The State of AI in Drug Discovery is entirely free. Sponsored by

David Baker’s Nobel Prize-winning lab has designed protein on/off switches as a tool for tunable cancer immunotherapies and biosensors.

AI-guided design of 16 functional bacteriophage genomes offers a path for phage-based therapies against antibiotic-resistant infections.

The open-source pipeline designs proteins with improved success rates for therapeutic targets, including gene editing proteins and allergens.

OpenCRISPR-1, an AI-generated custom gene editor capable of precision editing of the human genome. is just the beginning of Profluent’s AI applications.

VISTA, an AI-controlled data loop system, guides large-scale antibody design from scratch for applications in cancer therapy.

David Baker’s lab has successfully designed binders to disordered proteins, expanding therapeutic access to over 50% of the human proteome.

While AI-driven approaches tout increased speed and lower costs, commercial interests compromise scientific collaboration.

The open benchmark competition will evaluate the ability of AI-powered virtual cell models to generalize to new cell contexts for therapeutic applications.

The AI unicorn's Perturb-seq atlas is publicly available and detects dose-dependent genetic effects to enhance predictive power for drug discovery.

BaseData aims to improve AI models in biology by offering a 10-fold expansion of protein diversity compared to all public databases combined.

The MIT model predicts molecular binding affinity at newfound speed and accuracy, offering a powerful tool for commercial drug discovery.

Debates over AI antibody design terminology have clouded the industry’s shared mission of bringing better therapeutics to the clinic faster.

Imprint has raised $15 million to decode the body's immune memory for understanding chronic diseases, such as long-COVID and psychiatric disorders.

Treated with an individualized gene-editing therapy that corrects mutations directly on the genome, a patient shows improvement from a rare metabolic disease.

Trained on data covering 1.5 billion years of evolution, CZI’s new generative AI model probes cellular biology across species for therapeutic applications.

Researchers have developed a machine learning model that predicts Cas9 proteins that can be tailored with designer properties for therapeutic use.

Evo 2 now includes information from humans, plants, and other eukaryotic species to expand its capabilities in generative functional genomics.

Using protein structure prediction tools, researchers have uncovered receptor structure-function relationships to improve cell therapies.

Cerebral cavernous malformation (CCM) patients treated with oral drug, REC-994, showed reduction in total cerebral and brainstem lesion volume.

Cerebral cavernous malformation (CCM) patients treated with oral drug, REC-994, showed reduction in total cerebral and brainstem lesion volume.