https://variational.ai

Variational AI - We discover novel drug-like small moleculesWe are a team of AI/machine learning and business specialists using advanced generative AI for drug discovery. We collaborate closely with biopharmaceutical partners to develop new therapeutics across disease areas, aiming to positively impact lives.Variational AI - We discover novel drug-like small molecules Our ApproachCompanyTeamJobsWhat’s NewBlogContactWhy screen when you can create? Novel and selective lead structures in about a week or two through the power of generative AI.The Enki™ Platform is the first commercially accessible foundation model for small molecules.Access now available for more than 300 GPCR and kinase targets with more being added regularly.Request Access Enki™ is designed to make generating novel molecule structures easy. Expand your imagination in 4 easy stepsNo data required. Just define your TPP and Enki does the rest. Enki is an ensemble of generative algorithms trained on decades worth of experimental data with proven results.Define your TPPSelect your on-target(s), off-target(s), and other properties in minutes. 150 kinases 177 GPCRs{{item}}The Enki™ Platform is the first commercially accessible foundation model for small molecules.Request AccessCompanyFounded in September 2019, we are a team of experienced AI/machine learning researchers and medicinal and computational chemists applying state of the art generative AI to drug discovery in close collaboration with biopharmaceutical partners to redefine the unit economics of drug discovery and development.Our TeamWe are a team of experienced AI/machine learning and business specialists applying state of the art generative AI to drug discovery in close collaboration with biopharmaceutical partners to bring new therapeutics to market across disease areas and positively impact lives.Handol KimMehran Khodabandeh, PhDAhmad Issa, PhDMarshall Drew-BrookJason Rolfe, PhDAli Saberali, PhDPeter Guzzo, PhDRoslynn Drewitt-LangeSara Ibrahim Omar, PhDNathania Takyi, MScBoard, Observers, and AdvisorsFrank ChangBoard MemberRobert N. YoungPhD, SAB Member (Medicinal Chemistry)Jennifer HamiltonPhD, Advisor (Strategy/Commercial)Todd FarrellAdvisor (Strategy)John BoylanPhD, SAB Member (Cell Biology/Oncology drug discovery)Mads DaugaardPhD, SAB Member (Oncology Biology)Alexander TropshaPhD, SAB Member (Cheminformatics)Nancy HarrisonAdvisor (Strategy/ Commercial)Artem CherkasovPhD, SAB Member (Cheminformatics)Funding, Partners & InvestorsFounded in September 2019, we are a team of experienced AI/machine learning and business specialists applying state of the art generative AI to drug discovery in close collaboration with biopharmaceutical partners to bring new therapeutics to market across disease areas and positively impact lives.In the PressCutting through the noise of machine learning for drug discoveryDrug Discovery TrendsGenerative Machine Learning Can Construct Smooth Chemical Search Spaces for Efficient Drug DiscoveryDrug Discovery & DeliveryFunding news: AI-fueled drug discovery startup and auto safety company raise cashGeek WireHandol Kim of Variational AI On The Future Of Artificial IntelligenceAn Interview With Tyler GallagherRecent News & EventsBlogWhy is QSAR so far behind other forms of machine learning, and what can be done to close the gap?QSAR models struggle with extrapolation compared to conventional ML tasks like image recognition. Machine learning generalizes effectively when structured to align with its problem domain, suggesting that improving QSAR models… Read more: Why is QSAR so far behind other forms of machine learning, and what can be done to close the gap?Blog100 AI-generated molecules are worth a 1,000,000 molecule high-throughput screenGenerative AI in drug discovery is showing promise by optimizing molecule searches beyond traditional methods. Variational AI’s Enki algorithm created 100 AI-generated molecules that outperform 1,000,000 in conventional high-throughput screening,… Read more: 100 AI-generated molecules are worth a 1,000,000 molecule high-throughput screenBlogApplicability domains are common in QSAR but irrelevant for conventional ML tasksTraditional QSAR models are limited to interpolation within known chemical spaces, restricting drug discovery. In contrast, modern machine learning excels at extrapolation, opening new possibilities for exploring untapped chemical compounds… Read more: Applicability domains are common in QSAR but irrelevant for conventional ML tasksView All News & UpdatesVariational AI is hiring!Please see open job listing below or contact us if you would like to join the team in the area of machine learning, computational medicinal chemistry, and business development.View PositionsOur ApproachCompanyOur TeamWhat’s NewBlogCareersContactFollow UsLinkedInX577 Great Northern Way, #240 Vancouver, BC V5T 1E1 Canada+1 604 761 7199info@variational.ai© Variational AI Inc.Terms  |  Privacy Policyenusen-US1730966863https://variational.ai

ތިޔަ ސައިޓް އެޑިޓް ކުރަންވީތަ؟

ތިބާ ކީއްކުރަނީ؟