1859’s discovery engine has the capacity to generate millions of active and inactive data points with embedded structure-activity relationships (SAR). To generate high-quality datasets, AI is used to inform diversity or focused library design of drug-like, combinatorial libraries, which are screened in biologically relevant assays with dose-response readouts. Ultimately, this results in high rates of true positive and true negative data points, and exceptionally high activity confirmation rates. This approach uncovers novel hits for multiple targets and modalities and constructs robust AIML models with the proprietary screening data generated.

The ability to rapidly produce high-quality datasets at scale to train AIML models opens doors for pursuing “undruggable” targets, novel modalities, and emerging resistance mutations, all with limited and sparse public data available. Beyond optimizing for potency and selectivity, advancements in AI can synergistically optimize molecules throughout the pipeline beyond hit finding, tackling drug metabolism, pharmacokinetics, toxicity and other necessary biological criteria.

Join this webinar to gain insights into how data disrupts the drug discovery paradigm and ultimately delivers new medicines to patients faster.

Join experts from 1859, Sara Thrall Cortese, PhD, Co-founder, Scientific Lead; Andrew MacConnell, PhD, Co-founder, Scientific Fellow; Deirdre Olynick, PhD, MBA, VP Partnerships and Portfolio, for the live webinar on Tuesday, December 5, 2023, at 10am PST (1pm EST).

For more information, or to register for this event, visit Powering the AI Revolution for Drug Discovery with High-Quality Empirical Data.

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