Better decisions make better molecules

“Designing compounds with optimal ADMET properties is a fundamental challenge in drug discovery. This is where predictive AI tools can have a real impact. By accurately predicting ADMET properties in real time, Inductive’s platform helps our chemistry team design higher-quality compounds before investing resources in complex synthesis.”

“Inductive’s predictions allow us to front-load critical ADMET insights and accelerate our design-make-test cycles. We've saved time and reduced costs by prioritizing the most viable and high-quality compounds for synthesis, making every design cycle more impactful. We also use their solubility model to ensure compounds will behave well in screening assays, speeding up each design cycle by predicting solubility rather than waiting for it to be measured.”

“We’re proud to collaborate with Inductive Bio, Cincinnati Children's, Baylor College of Medicine, Torch Bio, and Advanced Research Projects Agency for Health (ARPA-H) on this ambitious effort to apply AI/ML to improve safety and ADME-Tox prediction.”

“Integrating Inductive Bio's ADMET models into Nested's predictive platforms helped us to prioritize designs with optimal drug like properties. This allowed us to rapidly iterate and optimize lead compounds and address critical ADMET challenges.”

“Inductive has become an essential part of our design and prioritization workflow, helping us effectively balance ADMET tradeoffs in our designs, confidently screen out compounds unlikely to advance the program, and streamline our testing cascade thanks to their spot-on permeability predictions. Inductive’s intuitive interface has also expanded participation in compound design discussions, leading to stronger decisions with every design cycle.”

“The Inductive ML platform has greatly aided the optimization of ADMET properties for our lead program. As a small biotech company, it is great to leverage thousands of consortium data points to help drive the design of improved molecules. The platform interface is extremely user friendly and provides a great tool for the chemistry team to rapidly model and communicate ideas. The Inductive team, including a ‘chemist in the loop’ and ML engineer, is also actively engaged and have greatly facilitated the use of the tools and made substantial contributions to the design process. All combined, the Inductive platform and team have helped Belharra to rapidly progress our lead program.”

“We use Inductive in the discovery design process to bring an early focus on compound properties with the aim to avoid designing suboptimal molecular features that can cost time and money down the line to correct. Inductive’s ADMET models, especially for metabolic stability, have become a core part of how we triage ideas and prioritize the most promising molecules. It’s not about replacing intuition, it’s about removing bias and seeing around corners to move faster and with more confidence.”

“We have been impressed by Inductive Bio and the quality of their ADMET models for some time, which is why we selected them as a partner to help accelerate our next-generation, CNS-penetrant HDAC6 inhibitor program. By combining Augustine Therapeutics’ differentiated HDAC6 inhibitor chemistry with Inductive’s embedded experts and advanced AI/ML capabilities, we aim to move faster and with greater confidence as we work to develop new therapies for neuromuscular and neurodegenerative diseases.”

“Inductive Bio has one focus: using AI to help medicinal chemists design better molecules. We're making fewer molecules to get better answers, saving cost and time on the way to a development candidate. Their models keep getting more predictive of our own in vitro ADME data. It's a low-cost, easy service to work with, and we plan to keep going.”

“Light Horse has been pleased to collaborate with Inductive Bio and integrate their innovative platform into our research workflows. The InductiveBio team has developed an impressive tool for predicting small molecule ADME properties that generates a meaningful insight ‘on the fly’. This highly practical and user friendly tool includes insights into early human PK predictions, thus enabling our researchers to make more informed trade-off decisions with greater speed and confidence. Beyond the strength of the technology itself, the Inductive Bio team has been exceptionally responsive, collaborative, and open to feedback. Their willingness to engage closely with our users and continuously improve the platform has made them a valuable partner.”

“Inductive’s ADME prediction tools have become an essential part of our compound design workflow, especially for the prediction of permeability and bioavailability. The interface is intuitive and easy to adopt and has made ML-guided prioritization a seamless part of our structure-based design process. Compass helps us make more informed decisions at each design cycle.”

“Inductive Bio's models help us allocate synthetic resources efficiently by prioritizing compounds with favorable properties and avoid making those that are likely to be insoluble, impermeable, or metabolically unstable. We've been impressed with the accuracy and reliability of model performance even for highly novel scaffolds with no literature precedents. The Compass software really stands out for its intuitive design, is fun to use, and easily integrates into our design workflows. The Inductive team is also super responsive - they proactively monitor model performance and deliver weekly updates as new data is generated, ensuring that we always have the most reliable tools to drive design decisions.”