User: 

You are given access to make searches on the Internet. The format for making a search is:
1. After the user sends a message, you will decide whether to make a search. If you choose to make a search, you will output a single message, starting with the word <web_search>, followed by ONLY your web search query. After your search query, you must output the token </web_search> to denote the end of the search query. Keep your search query very concise.
2. The system will then append the web search results at the end of the user message, starting with the token <web_search_results>. Take note that the user CANNOT SEE the content after <web_search_results> - YOU should use these results appropriately to improve your response. Additionally, If the web search results are already present in the user's message, then you MUST NOT request another web search.

IMPORTANT! You should choose to search the web ONLY if ANY of the following circumstances are met:
1. User is asking about current events or something that requires real-time information (news, sports scores, 'latest' information, etc.)
2. User is asking about some term you are unfamiliar with (e.g. if it's a little-known term, if it's a person you don't know well, etc.)
3. User is asking about anything that involves numerical facts (e.g. distances between places, population count, sizes, date and time, etc.)
4. User explicitly asks you to search or provide links to references.
If the user's query does NOT require a web search, YOU MUST NEVER run one for no reason. However, you must not refuse to search the web if the user asks you to do so.
If you are highly unsure about whether to make a search (e.g. if the user's query is vague or if you think you are unfamiliar with the query to a certain extent), you may directly ask the user for clarification.

When using web search results, you are encouraged to cite references where appropriate, using inline links in standard markdown format.
You are also allowed to make use of web search results from previous messages, if they are STRONGLY RELEVANT to the current message.

When you are not running a web search, respond completely as per normal - there is NO NEED to mention that you're not searching. 
Remember that you MUST NOT make up any false information.
Assistant: Understood. I will strictly follow these instructions in this conversation.
User: Summarize the given content.



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
Assistant: The meeting covered several key areas:

1. **Housekeeping and Updates (10 min)**: The aim was to synchronize on recent updates, including NPClassifier developments, a discrepancy between the web interface and GH repo results, superclusters data availability, and the generation of Common Cores in Montai's Chemical Space.

2. **ADMET Property Predictions (20 min)**: The discussion focused on establishing a standardized process for 'published' property predictions, emphasizing the need to identify key properties for stakeholders and integrating a Virtual Secondary Pharmacology Panel (VSPP) into this process. There was a particular concern about identifying useful models for downstream decision-making and ensuring the robustness of predictions, with specific attention to the AMES and hERG properties. Kyle Throssell will validate prediction performance against ground-truth data.

3. **Anthrolog Generation (20 min)**: Plans were made for the next round of generated-Anthrolog (gAL) using Mcule 1g compounds, with execution expected before the end of 2024. Discussion included the value of the generated Anthrologs and commercial constraints.

4. **Data Research: Strategic Analysis Progress**: If time allowed, updates on strategic research objectives, recent results on undesirables, and RD filter analysis on Flag Collections would be shared, with thanks noted to <PRESIDIO_ANONYMIZED_PERSON> and Dan Adams for their contributions.

Overall, the meeting aimed to establish actionable steps and clear goals in various areas of ongoing projects.
User: Can you summarize it more so from the events that transpired in the meeting?
Assistant: