Healthcare & Life Sciences
Top 10 AI tools to design molecular candidates
Evidence ranking
- 1
Vecura
Adoption
Who uses it?
“A global consumer health leader required plant-derived solutions for mental wellness (focus and stress).”
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A global consumer health leader required plant-derived solutions for mental wellness (focus and stress).
Read source · www.nyb.group ↗
Customer satisfaction
Are customers happy with it?
“Validated activity across 156 neuromodulatory receptors.”
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Validated activity across 156 neuromodulatory receptors.
Read source · www.nyb.group ↗
Value for money
Are the benefits worth the cost?
Popularity
How much interest does it attract?
Coming soon
Product-specific search-interest measurement is not available yet.
- 2
AbBFN2
Documented workflow
“We believe that by unifying these tasks into a single generative framework, AbBFN2 has the potential to enhance efficiency, empowering scientists to optimise multiple antibody properties simultaneously. What is AbBFN2? Built…”
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We believe that by unifying these tasks into a single generative framework, AbBFN2 has the potential to enhance efficiency, empowering scientists to optimise multiple antibody properties simultaneously. What is AbBFN2? Built…
Read source · deepchain.bio ↗
- 3
FAST
Documented workflow
“ML models trained on sequence-activity data, including negatives, rank the library and unveil non-obvious agonists. Generate ML models design new agonists beyond the experimental input library. In our CB2 program, designed…”
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ML models trained on sequence-activity data, including negatives, rank the library and unveil non-obvious agonists. Generate ML models design new agonists beyond the experimental input library. In our CB2 program, designed…
Read source · www.abalonebio.com ↗
- 4
Halmos
Documented workflow
“us.Evaluate and optimize my assayDesign a model for fungal metabolismChoose the DoE for a process studyWork out why two datasets disagree ExampleGenerate a personalisedmRNA vaccinefor this cancer patient.We gave Halmos one…”
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us.Evaluate and optimize my assayDesign a model for fungal metabolismChoose the DoE for a process studyWork out why two datasets disagree ExampleGenerate a personalisedmRNA vaccinefor this cancer patient.We gave Halmos one…
Read source · halmoslabs.com ↗
- 5
ITO™ Platform
Documented workflow
“We integrate massive multimodal data, frontier Al models, and high-throughput lab automation to design small and large molecule therapeutics better and faster than traditional approaches. Swipe up to learn how... Scroll to…”
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We integrate massive multimodal data, frontier Al models, and high-throughput lab automation to design small and large molecule therapeutics better and faster than traditional approaches. Swipe up to learn how... Scroll to…
Read source · www.1910.ai ↗
- 6
Molecular Engine
Documented workflow
“MAUD 1.0’s physics-based generative AI uses the target protein model as input to perform iterative, multi-parameter design cycles that optimize multiple drug-like properties simultaneously, enabling the discovery of potent,…”
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MAUD 1.0’s physics-based generative AI uses the target protein model as input to perform iterative, multi-parameter design cycles that optimize multiple drug-like properties simultaneously, enabling the discovery of potent,…
Read source · menten.ai ↗
- 7
AAV Capsid Engineering
Documented feature
“A computational approach that leverages Protein Language Models (pLMs) and Reinforcement Learning (RL) to engineer AAV (Adeno-Associated Virus) capsids. By focusing on permutations within the variable region VIII, our model…”
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A computational approach that leverages Protein Language Models (pLMs) and Reinforcement Learning (RL) to engineer AAV (Adeno-Associated Virus) capsids. By focusing on permutations within the variable region VIII, our model…
Read source · whitelabgx.com ↗
- 8
AIMCADD®
Documented feature
“AI-Powered Drug Discovery: Collaborating with Experts to Drive Innovation AnHorn Medicines has developed AIMCADD ® , a cutting-edge generative AI platform that integrates artificial intelligence with expert scientific…”
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AI-Powered Drug Discovery: Collaborating with Experts to Drive Innovation AnHorn Medicines has developed AIMCADD ® , a cutting-edge generative AI platform that integrates artificial intelligence with expert scientific…
Read source · www.anhornmed.com ↗
- 9
Darwin model series
Documented feature
“Our Darwin model series enables the prediction of drug toxicity and efficacy across diverse populations and optimizes molecules for broader efficacy—addressing the hidden, microbiome‑driven causes of drug response and…”
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Our Darwin model series enables the prediction of drug toxicity and efficacy across diverse populations and optimizes molecules for broader efficacy—addressing the hidden, microbiome‑driven causes of drug response and…
Read source · anto.bio ↗
- 10
DrugFlow Platform
Documented feature
“target proteins through advanced AI algorithms, improving hit rates and accelerating drug discovery.Druglikeness PredictionEvaluate the absorption, distribution, metabolism, excretion and toxicity characteristics of…”
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target proteins through advanced AI algorithms, improving hit rates and accelerating drug discovery.Druglikeness PredictionEvaluate the absorption, distribution, metabolism, excretion and toxicity characteristics of…
Read source · drugflow.com ↗
