Remote Machine Learning Researcher Job at PostEra

Developing cures for diseases has a high rate of failure, is very time consuming, and very expensive.

The discovery of a cure follows three stages

1. Biology: Identify relevant biological target(s) associated with the disease.

2. Chemistry: Develop safe and effective chemical compounds that can hit those targets.

3. Medicine: Develop these compounds into medicines by showing their effectiveness in the appropriate patients in clinical trials.

The time taken to develop a drug is over 10 years and hasn’t improved over the last decade.

PostEra has developed Proton, an end-to-end machine learning platform to close the Design-Make-Test cycle of Medicinal Chemistry

PostEra’s current focus is on the Chemistry of drug discovery. Known as Medicinal Chemistry, it constitutes an iterative three-step cycle. At each stage of the cycle we use Proton to solve the key problems:

1. Design: What molecule should we make?

2. Make: How do we synthesize it?

3. Test: What are its properties?

All three stages are important though the Make stage, known as chemical synthesis, is typically the most time consuming step.

Protoncloses the full cycle by addressing the key challenges at each stage of the process:

• Design: Combining our proprietary data and low-data ML to design optimized molecules that satisfy the many competing properties that drug candidates must satisfy.

• Make: State-of-the-art synthesis and search ensuring that every molecule we design has a reliable synthetic route and that molecules can be made in parallel using shared synthetic intermediates.

• Test: Novel active learning methodologies to gather the most informative data at each cycle.

Proton allows PostEra to do faster drug discovery, find more optimized drug candidates, and develop better cures for patients.