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1. Housekeeping and Updates (10 min)
Goal: Ensure alignment on recent updates and housekeeping items to establish a clear starting point for discussions.

Updates for NPClassifier from CM.

Discrepancy between the web interface and the most recent GH repo results

Superclusters update from Duminda

Data has been generated and is in s3, 1 .pq parquets

Common Cores on Montai Chemical Space

Will be generated on all of CDD & entire commercial set.

2. ADMET Property Predictions (20 min)
Goal: Define a stable and stakeholder-approved process for 'published' property predictions and prioritize key properties for decision-making.

Proposal for establishing a process to create 'published' models for property predictions.

Discussion on refining and prioritizing the most relevant properties for stakeholders.

Incorporating Virtual Secondary Pharmacology Panel (VSPP) as part of the prioritization process.

NOTES: 

Discussion on refining and prioritizing the most relevant properties for stakeholders

Want to identify downstream stakeholders; filter properties for more development

VSPP + ClubMED use-case: Primarily a measure of promiscuity Secondary pharmacology often happens much later in the process than early discovery. MED would be more concerned with primary pharmacology before prioritizing on secondary pharmacology.

Usage depends on the robustness of the tools;

Could we identify models that are useful downstream in the discovery funnel

In some cases, liabilities are discovered as part of the funnel, but there are not many cases where there would not be many cases by which we would change the decision-making in a targeted fashion

MedChem/Lead-op perspective:We have encountered much promiscuity in our screening data; AMES and hERG are the most important properties

SafetyScan Assay: Test against 50 different targets for off-targets

These are included in VSPP (~22 models trained on public data)

Use of information would depend on the robustness of the predictions; the scale of SafetyScan does not 

Ability to run VSPP on the library would enable use this data at a scale we cannot do in-vitro, which can help us provide more general secondary information

What do we need to be “robust”?

Test against ground-truth data

Classifier and the need for accurate potency window: The relative effects of a compound on this vs the primary 

Desired benchmark accuracy should be something analogous to IC50 +/- 3-4x

NEXT STEPS:

@Kyle Throssell has access to SafetyScan data and will begin validating the performance of predictions against ground-truth data

3. Anthrolog Generation (20 min)
Goal: Plan the next round of generated-Anthrolog (gAL) generation and align timelines and expectations for gAL expansion before year-end.

Next round of anthrolog generation using Mcule 1g compounds as starting materials.

Timeline: Kickoff and execution before the EOY 2024.

Informing AG stakeholders and reflecting CTO’s expectations for gAL expansion.

Reference

NOTES:

What is the value of the ~3B gALs?

We are still constrained by what we can get commercially

Are we able to prove that the gALs 

 

4. Data Research: Strategic Analysis Progress (Time-permitting or async)
Goal: Share progress updates and analyses if time permits, focusing on actionable insights and stakeholder contributions.

If time permits:

Research progress from DR on strategic learning objectives

Review of undesirables' most recent results.

RD filter analysis on the Flag Collections

With thanks to @Rody Arantes and @Dan Adams for setting these up!

check mark button Action items
@Kyle Throssell has access to SafetyScan data and will begin validating the performance of predictions against ground-truth data