We have applied our machine learning capabilities to build endocrine disruption models for global consumer product companies, and ADME models for a large rare disease company. We work with CROs-modeling in vivo animal data, make predictions with target models and predict ADME data to advance their internal drug discovery efforts. We have red-teaming capabilities for testing new AI technologies.
If your company is interested in leveraging our technologies, drug discovery capabilities or licensing our software or molecules then please connect with us and discuss how we could partner.
What We Do
We develop potential therapeutics through our extensive researcher and foundation networks.
We identify research that can be readily translated to treatments for rare and neglected diseases.
We provide the drug discovery preclinical and clinical expertise to move therapeutics towards the clinic.
We can help you by providing our expertise for your grant submission.
How We Report
Understand what the customer wants
Understand the problem and not just what our models can do
Clearly describe what we did:
- What did we find?
- How does this benefit the company?
- How can we build on this work for the company?
Provide graphical representations of the data
Highlight the advantages and acknowledge limitations
What We Have Delivered
We have obtained 9 orphan drug designations .
We have delivered measurable results for our collaborators and clients.
We have widely published our results in respected peer reviewed journals.
Client Use Cases
Chemicals
- Company needed a commercial read across tool integrated with machine learning models for regulatory filings
- We developed a new tool that used the EPA software and data in a secure environment
- We enable the company to predict how their molecules are likely to behave when the EPA does read across so they can anticipate their questions
DNA-encoded Library Company
- Company needed a way to score 1bn molecules for toxicity properties
- We developed an approach to screen 1bn molecules in a few hours
- We also developed a toxicity screen with 42 properties
- Generated a massive amount of data that enabled the company to raise a VC $30M A round
Drug Discovery
- Client needed new linkers for PROTACS with ideal predicted properties
- We developed a generative design approach to design linkers and predict solubility
- Provided new ideas, IP to client
- There is no commercial tool to do what we provided
Consumer Products
- Curated data on endocrine disruption (ER, AR, Aromatase) built models and predicted for their 1000s of ingredients
- Enabled them to prioritize ingredients for in vitro testing
- Saved them significant time and $ in testing compounds - also reduced animal usage
- Published papers, talks at conferences, showed thought leadership for client
CONTRACT MACHINE LEARNING
Collaborate to Accelerate Drug Discovery
- We sign a confidentiality agreement
- We send you a quote for the work
- You send us the molecules of interest
- We send you the predictions and applicability domain data etc.
Interested?