Discovering drugs that show therapeutic potential is difficult, time-consuming, and expensive. But of those found, it is harder still to find those drugs which do not also have severe side effects and can pass through clinical trials.
We look at historically failed clinical trials to identify the most promising targets as well as internal projects that were abandoned.
By focusing on safety problems that occur in Preclinical, Phase 1, or Phase 2 trials, we are able to identify the most promising drugs, turn them around quickly, and get them to patients faster than starting drug discovery from scratch.
Our proprietary AI model, SAFEPATH, applies deep learning to our combined bioinformatics and cheminformatics datasets to solve drug safety issues.
In preclinical and clinical studies, safety assessments typically reveal what went wrong—such as liver damage or heart issues—but fail to explain why these issues occurred, or how they might be mitigated.
SAFEPATH is a first-of-its-kind AI platform that combines advanced machine learning models with a multimodal data approach to enable a deep understanding of toxicity mechanisms, and offers actionable insights to facilitate drug turnaround.
Sam has a broad, hands-on track record with transforming healthcare which he brings to his role as CEO at Ignota Labs. He was part of the consulting team shaping commercialisation strategy for Google DeepMind's AlphaFold, influencing government policies and spearheading international healthcare data collaborations.
He also advised a wide variety of healthcare and government clients as part of his consulting roles at MSD and The PSC, among others. During university, he achieved a first class degree and was the top student his year in mathematics and went on to study for his PhD in algebraic geometry, although decided to leave to pursue a career in industry. After consulting, Sam decided to go for an MBA at INSEAD, earning the Dean’s List distinction and graduating in the top 10% of his class. He has been the driving force behind early partnerships, business model innovation, and early revenues, and has quickly extended the reach of Ignota Labs within the pharma space.
Dr. Hosseini-Gerami bridges the worlds of chemistry, biology, and AI in her role as Chief Data Science Officer at Ignota Labs. She has an undergraduate and masters degree in chemistry, winning Outstanding Graduate of the Year and was a finalist in the prestigious Salters awards. She then went on to earn a PhD at the University of Cambridge under the mentorship of Andreas Bender, a renowned figure in AI drug discovery. There she pioneered integrative cheminformatics and bioinformatics strategies for understanding drug molecular mechanisms, winning the Chemistry Theory Outstanding Thesis Award in 2023, and producing several publications in collaboration with Eli Lilly, leading industry translation of her academic research.
At Ignota Labs, she has built upon these sophisticated methods to understand the mechanisms of drug toxicity and how to mitigate them. Her goal is to leverage AI not just to understand, but also to prevent adverse drug reactions, ensuring safer therapeutic options for patients.
Dr. Jordan Lane has extensive experience in the AI drug discovery space and is driven by a profound commitment to revolutionizing drug discovery; integrating artificial intelligence with bioscience to enhance drug safety and efficacy. At Ignota Labs, Dr. Lane leads innovation; leveraging his extensive background in biochemistry, genetics, and AI to pioneer transformative treatments in global patient care. His journey began at the University of Nottingham, where he earned a BSc in Biochemistry and Genetics, followed directly by a PhD focused on Alzheimer's Disease.
Dr. Lane's early academic success included contributing to over 15 works in the field. His work led to strategic roles in the biopharmaceutical industry, from developing oncology assets at AstraZeneca to spearheading AI-driven drug discovery projects at LabGenius and BenevolentAI. His career is marked by a relentless pursuit of excellence, interdisciplinary collaboration, and a visionary approach to the future of medicine.
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