Deborah Palestrant

The Drug Discovery Biology & Bioinformatics Strategy Meeting East Coast on May 14th brings Gregory Williams, Curia's Senior Research Scientist II, to Princeton. Prepare to explore how emerging technologies and platforms can be harnessed to unlock a broader target space for drug discovery. Dr. Williams will also delve into strategies for efficiently validating promising targets and ensuring their therapeutic potential. We'll explore the crucial role of target specificity and selectivity in the drug discovery process, along with the methods used to assess these factors. The session will unveil the power of computational modeling and artificial intelligence in identifying novel drug targets and predicting hit efficacy. Dr. Williams will address the challenges of target identification in complex diseases with multiple pathways and targets. He'll also discuss strategies for overcoming target redundancy and prioritizing those with the highest therapeutic potential. Currently leading Curia's Cell-Based Assay Technologies team, Dr. Williams is a key player in driving innovative pre-clinical drug discovery programs. This session promises to be a goldmine of insights for anyone navigating the complexities of target identification. Stay tuned for more! #ClinicalTrials #DrugDiscovery #TargetIdentification #EastCoastScience #GregWilliams #CBAT #StrategyMeeting

1

Recursion and Exscientia have entered into a definitive agreement to create a global technology-enabled drug discovery leader with comprehensive capabilities. This merger combines Recursion’s biology exploration and translational capabilities with Exscientia’s precision chemistry design and automated synthesis expertise. The goal is to utilize advanced life sciences and technology to deliver treatments more efficiently and at a lower cost compared to traditional methods. The combined business is well-capitalized, with approximately $850 million in cash and cash equivalents, and expects to achieve annual synergies exceeding $100 million. The partnership will also enhance their pipeline, with around 10 clinical readouts anticipated over the next 18 months and potential milestone payments of $200 million over the next two years. 🔸 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐧 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 𝐚𝐧𝐝 𝐏𝐡𝐚𝐫𝐦𝐚𝐜𝐲: The implications for healthcare and pharmacy are noteworthy, as this merger aims to streamline the drug discovery and development process. By integrating high-throughput biology and advanced chemistry automation, the new entity seeks to improve the efficiency of developing high-quality medicines. This approach may reduce drug development timelines and costs, ultimately benefiting patients with quicker access to new therapies. The collaboration with leading biopharma companies, such as Roche-Genentech, Sanofi, Bayer, and Merck KGaA, highlights the potential for advancements in oncology, rare diseases, and infectious diseases, positioning the combined company as a significant player in the biotechnology industry. 🔗 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐑𝐞𝐜𝐮𝐫𝐬𝐢𝐨𝐧 𝐏𝐫𝐞𝐬𝐬 𝐑𝐞𝐥𝐞𝐚𝐬𝐞: https://lnkd.in/eTSEfuYv #DrugDiscovery #BiotechInnovation #HealthcareAdvancement 🌐 Swenson Pharmacy Advisors (SPA) 𝐖𝐞𝐛𝐬𝐢𝐭𝐞: https://lnkd.in/gWFbVAjz

2

2 Comments

Evotec is excited to preview an exciting novel approach to de novo #ProteinDesign that allows for prediction and generation of #biocatalysts using only a desired chemical reaction (SMIRKS) as a prompt, ALCHEMIST: A Novel AI for Biocatalyst de novo Design and Discovery. The ALCHEMIST #AI can generate relevant and diverse protein designs for use as biocatalysts or as indicators of what a wild-type enzyme catalyzing novel #chemistry would likely look like. Whatever your #biocatalysis or #greenchemistry needs, we have the solution. How can Evotec help you today? https://hubs.ly/Q02FPXLL0

161

6 Comments

Risk v. Return Investment Profile: ImmunoPrecise Antibodies Ltd.(NASDAQ: IPA $0.625) CFP has had the opportunity to review Carl Kestens' Fair Value Analysis of ImmunoPrecise(attached below). CFP would encourage all of you to review it as well. CFP's key takeaways and comments are: 1. ImmunoPrecise has a Market Cap of approximately $18 million USD, which is extremely cheap relative to any market evaluation technique you use. 2. IPA has several potential growth drivers that have yet to deliver value to the company. 3. We agree that many investors have given up(lost patience) on the prospects of any of these potential events will actually be achieved. Expectations of Investors have not been met by the Company to date. Herein may lie the opportunity moving forward... 4. IPA has finally addressed its non-existent Capital Markets Strategy with an experienced, and seasoned group out of New York City over the last couple of weeks. 5. The NYC Group is also addressing the Company's Communication, Media, and Investor Relations Strategy. The new messaging(which should have always been in place) is under promise, and over deliver(exceed expectations) go forward. CFP has already seen improvement in the messaging to "simplify" the story to prospective investors. 6. The investment risk/return profile today looks very compelling. It reminds me of some old investment advice: "buy when everyone is selling and sell when everyone is buying." Disclaimer: This is posted for information purposes only. Please consult your investment professional for investment advice. Capital Find Partners owns shares in ImmunoPrecise. IPA (ImmunoPrecise Antibodies) BioStrand (a subsidiary of IPA) InterSystems Quantum Media Group, LLC #LENSai #Biotech #ai #HYFTs #HYFTTechnology #drugdiscovery #healthcare #pharma #personalizedmedicine #omics #AIDrugDiscovery #systemthinking #bioinformatics #antibodies #machinelearning #multiomics #LLMs #datascience #computationalbiology #nlp #ontologies #semantics #knowledgegraphs #lifesciences #bigdata #informationinformationdilemma #patternrecognition #insilico #molecularbiologists #aminoacids #dna #rna #HYFTpatterns

12

3 Comments

FAbCon: Can antibody-specific generative foundation model facilitate antibody sequence understanding? A team led by Jacob Galson has just released FAbCon, a set of generative large language models (LLMs) for antibody binding prediction and design. The FAbCon LLM is a specialized model that comprises 2.4 billion parameters based on Falcon, an LLM for natural language processing applications. The collection of human antibodies forms a uniquely diverse and large class of proteins that caters for the wide range of antigens that the human body would be exposed to. The capability to decode the language of human antibodies would enable deeper understanding of diseases and the consequent ability to treat them in a targeted manner. LLMs offers the ideal capacity to analyze and encode the patterns in the large antibody sequence corpus, with the possibility to scale performance with model size. FAbCon is a decoder-only antibody-specific LLM comprising more than 2 billion parameters built on Falcon, an LLM for natural language processing. FAbCon also shares some similarity to other state-of-the-art generative protein language models like ProGen2 and ProtGPT2. 🔢 FAbCon was pre-trained on paired (heavy and light chains in a single sequence) and unpaired (heavy or light chain only) antibody sequences, following which the model exhibited a mature representation of antibody sequences that enabled its utility for diverse antibody modeling and design tasks. FAbCon consists of three models of varying number of parameters: 1️⃣ FAbCon-small (144 million parameters) 2️⃣ FAbCon-medium (297 million parameters) 3️⃣ FAbConlarge (2.4 billion parameters) The models have been specifically evaluated for antigen binding prediction and antibody design capabilities. All the models can handle heavy-chain only, light-chain only, and paired chain inputs. 💉 The FAbCon models were fine-tuned for binding predictions on datasets of three antigens: HER2, SARS-CoV2 spike peptide, and IL-6. FAbCon-large demonstrated the best performance based on AUPR and AUROC metrics, outperforming existing models. 🏃‍♂️ On generative de novo antibody design task, FAbCon-large surpasses ProGen2-OAS based on OASis score, a measure of humanness of generated antibodies. ❓ How does FAbCon’s generative capability for designing new antibodies compare with traditional biologics discovery methods in terms of speed, cost, and success rate in identifying viable manufacturable therapeutic candidates? ❔ What are the specific challenges that need to be addressed to integrate this model effectively into the current drug discovery pipeline? Paper: https://lnkd.in/gbPwJpaK Models (huggingface): https://lnkd.in/gVGV8RKN #Machinelearning #Deeplearning #LLM #drugdiscovery #structuralbiology #pharmaceuticals

26

The promise of TechBio. Investment firm DCVC has released its Deep Tech Opportunities Report highlighting the areas where they see the most promise and potential, from robotics and quantum computing to defense, TechBio, TechMed and drug discovery. ▪ The report notes that when it comes to TechBio, which they define as “a new branch of the AI industry that constructs proprietary biological and chemical datasets to fuel advanced computation and raise the hit rate in drug discovery,” the biggest bottleneck has been the complexity of biology itself. ▪ But by gathering data in a systematic, automated way and using in silico modeling, they write that companies can now make increasingly precise predictions, much faster and cheaper than traditional drug discovery. ▪ The report notes that Recursion “started doing TechBio long before there was a common term for it” and focused efforts on amassing the largest collection of biological and chemical fit-for-purpose datasets in order to drive new discoveries – a collection that has now grown to over 50 petabytes of data – “including phenomics data showing how toxins, pathogens, genetic changes and candidate drug molecules affect the morphology of individual cells.” ▪ “They have one of the biggest data sets out there, which puts them at the vanguard of the data race in biopharma” says Zachary Bogue. 👉 Read the full report here: https://lnkd.in/e76eUvVe #ai #deeptech #techbio #opportunities #data

88

A recent publication from Park et al. at the University of Illinois Urbana-Champaign features Fluigent pressure controllers in a study to develop and demonstrate a nanodialysis (ND) sampling probe adapted for microdialysis sampling. The use of droplet techniques enhances the temporal resolution of the sampling technique and has applications for chemical sampling in biological tissues. Read the paper: https://lnkd.in/eMuA5D8U Learn more about Fluigent pressure controllers: https://lnkd.in/ge-SWWiU    #microfluidics #neuroscience #pharmacology #bioengineering #pressurecontrol

2

High-resolution epitope mapping of VHH-Fc-VHH bispecifics coming in hot below! Recently published paper by #Twist Biosciences features our structural work on a bispecific antibody with four VHHs. Obtaining structural information for multi-valent VHH-based antibodies can be challenging due to their smaller size and unique and flexible binding configurations. We successfully obtained a CryoEM map that showed three VHHs binding in a "two-up, one-down" configuration on the receptor binding domains (RBDs), with one VHH on each RBD. Achieving good resolution required intensive focused refinements due to the small size of the VHHs (~15 kDa). The findings were intriguing, revealing subtle differences in the epitopes when identical paratopes bind to RBDs in up or down configurations. Read more about the exciting findings and the potential for combating SARS-CoV-2 antigenic drift: https://lnkd.in/eaHeHf4f #Research #Antibodies #CryoEM #StructuralBiology

9