II: TechBio News Day 👾
🗂️: Oxford Cannabinoid Technologies, DiaGen, Noetik, CellCarta, Lunaphore, Tevogen Bio, Nucleai and Synaffix & BigHat
Hi everyone, for this week’s update 👉🏼
🗂️: 10x Genomics, Elsevier, Insilico Medicine, IPA, J Ints Bio, Model Medicines, Antiverse and inCerebro
II: TechBio News Day 👾
🗂️: Oxford Cannabinoid Technologies, DiaGen, Noetik, CellCarta, Lunaphore, Tevogen Bio, Nucleai and Synaffix & BigHat Biosciences
🗂️: Research Grid, Quantiphi & DDReg, PicnicHealth, Lantern Pharma, Concr & CariGenetics, Voima Ventures, InnophAI and Vilya
“Any fool can know. The point is to understand.”
By Albert Einstein
II: TechBio News Day 👾
👾 Oxford Cannabinoid Technologies Ltd
On November 4, 2024, Oxford Cannabinoid Technologies (OCT) announced the successful completion of 'proof of concept' of its AI-enabled drug discovery asset, which it is developing in collaboration with New York-based tech consultancy, Hypatia AI (OCT announces exclusive Joint Development Agreement with ex-Google AI experts, Hypatia AI). Hypatia is developing a cutting-edge AI tool that will significantly accelerate OCT’s drug discovery process by focusing on deep, rigorous insights from the vast scientific literature, ensuring OCT’s scientific team spends less time searching and more time discovering.
Focusing on OCT's proprietary and patent-protected library of over 500 modified cannabinoid derivatives, which are classed as new chemical entities (NCEs), the new asset in development augments the literature search and review capabilities of the company’s scientific team, taking advantage of large language models to build knowledge graphs and highlight connections across a vast and complex literature at unparalleled speed and scale.
Oxford Cannabinoid Holdings Plc is the holding company of Oxford Cannabinoid Technologies Ltd, a UK-based biotech company that has a range of compounds in drug development, including proprietary cannabinoid derivatives, phytocannabinoids and completely new chemical entities (NCEs) that target the endocannabinoid system. They completed their Phase I single-ascending-dose clinical trial for Programme 1 (OCT461201) last October, with no safety or tolerability concerns, and are now well positioned to commence their second one (The science behind OCT). Programme 1 is targeting peripheral neuropathies such as chemotherapy-induced peripheral neuropathy (CIPN), a challenging complication arising from treatment with many commonly used anti-cancer agents. While Programme 1 focuses on peripheral neuropathies, their second programme (OCT130401) targets Trigeminal Neuralgia (TN). TN is a debilitating neurological disorder that affects the trigeminal nerve, a cranial nerve responsible for sensation in the face which is vital for everyday motor functions such as biting and chewing. OCT130401 (Programme 2) is in development and is due to be trialed as a treatment for TN. It has already completed its pre-clinical development and is ready to commence its Phase I clinical trials.
In addition to Programmes 1 and 2, they have already undertaken preliminary research on Programme 3 which is focused on a range of potential neuropathic pain indications, as well as Programme 4, which is aimed at an oncology target.
👾 DiaGen AI Inc
On November 7, 2024, DiaGen announced a partnership with Mila, the Quebec Artificial Intelligence Institute, a world-renowned network of experts and researchers in AI and ML (DiaGen AI and Mila Announce Partnership to Scale Protein Design in Diagnostics and Drug Discovery). By collaborating with Mila, DiaGen’s team led by Dr. Eldad Haber and Mohit Pandey, will accelerate the design of bespoke therapeutic proteins to optimize key properties such as stability, synthesizability and target binding, making an impact on human longevity and other critical areas of healthcare including cancer and immune disorders.
Founded in 2021, DiaGen (Canada) seeks to advance a diverse pipeline of AI drug discovery solutions, focusing on protein and peptide design, vaccine development and diagnostics for health wellness, longevity and precision medicine. Its AI engine (Día) has garnered endorsements from industry leaders. Diagen AI (formerly Proteic) is an AI-driven protein design platform developing new biological molecules to re-shape the health market.
👾 Noetik Inc
On November 07, 2024, Noetik just announced the first two presentations of its AI-enabled drug discovery platform at Society for Immunotherapy of Cancer (SITC) 39th Annual Meeting (Noetik Announces First-in-Class Human Foundation Models for Discovery at SITC 2024). The two posters showcase Noetik’s OCTO foundation model of cell and tissue biology and demonstrate for the first time the application of OCTO to therapeutics discovery 👉
They have created a platform to generate multimodal data specifically for self-supervised ML, from Tissue Microarrays (TMAs) from formalin-fixed paraffin-embedded (FFPE) tissue blocks, using three platforms: 16-channel multiplex Immunofluorescence (mIF), 1000-plex spatial transcriptomics (NanoString CosMx) and hematoxylin-eosin (H&E). Then they used this large-scale, multimodal data to train custom transformer models.
In total, they generated multimodal data on 1000 non-small cell lung cancer (NSCLC) samples, and trained models on the full dataset.
Inspecting the embedding space of one model at the patient level, they found that patient samples separate by known ‘immunotypes’ such as T cell infiltrated/desert, and that more nuanced separation can be teased apart to reveal novel tissue immunotypes. Additionally, using the model’s ability to answer biological therapeutic counterfactuals, they have uncovered potential novel therapeutic targets for increasing CD8 T cell infiltration in the tumor and enhancing the efficacy of T cell killing.
They then crafted a platform to create multimodal data purpose-built for AI.
With this data, they have trained large-scale models that can be used for defining patient populations and identifying therapeutic targets.
Tertiary Lymphoid Structures (TLS) are aggregates of immune cells that form at sites of chronic inflammation. Presence of tumor-associated TLS has recently been shown to associate with immune checkpoint inhibitor response independent of known biomarkers.
Accordingly, they have built a spatial atlas of over 1000 non-small cell lung cancer (NSCLC) tumor tissues encompassing multiple paired modalities: subcellular resolution spatial transcriptomics from CosMx (the most flexible and robust spatial single-cell imaging platform), 15-plex immunofluorescence images, hematoxylin-eosin stain images and whole exome sequencing. They trained a multimodal foundation model on this dataset and then queried the model to propose pixelwise TLS segmentation masks based on predicted probabilities. Paired spatial transcriptomics data were then used to identify genes colocalized with TLS. Finally, they used the foundation model to perform in silico perturbation of genes to simulate their downstream biological impact.
They detected TLSes in approximately 40% of the lung tumors with high specificity and they found the presence of TLS is associated with elevated immune infiltration in tumors. They also found that the spatial gene expression profile differs between TLS-associated tumor microenvironment (TME) and TLS-free TME. Genes known to modulate lymph node organogenesis (e.g. lymphotoxin beta, LTB) are associated with TLS, along with gene sets related to lymphocyte activation and immune response. They also identified genes that promote TLS maturation.
In silico gene perturbations using this model revealed potential targets that may promote TLS formation and impact immune cell infiltration through modulating cell-cell communication.
In conclusion, TLS can be identified and segmented efficiently with a multimodal foundation model. TLS associated genes are expressed in various tissue compartments and form a complex cellular communication network. These genes play a big role in activating anti-tumor immunity. In silico perturbation of these genes reveals potential targets that may promote anti-tumor response through TLS induction.
Noetic is an AI drug discovery company leveraging spatial data (being the biggest user of two new platforms from two different spatial companies—one for proteomics and the other for transcriptomics) to develop cancer immunotherapies, and was launched with $14M seed financing from two former leaders of Recursion Pharmaceuticals hoping to bring a data-obsessed mentality to cancer research. Noetik combines self-supervised learning with the industrial-scale generation of human multimodal data.
In 2023, Noetik announced the pairing of their multimodal human data atlas with an innovative in vivo functional genomics platform to power the development of precision cancer immunotherapies (Noetik Launches "Perturb-map" In Vivo Functional Genomics Platform and Adds Precision Immunology Leader Brian Brown, Ph.D. to Scientific Advisory Board). The platform builds on Perturb-map, a groundbreaking spatial functional genomics technology that allows pooled parallel analysis of hundreds of genetically modified tumor clones in a single experiment. Noetik’s platform will evaluate the impact of genetic variants at an unprecedented in vivo scale. The company is currently generating an initial dataset of >650 mutations in a preclinical model of lung cancer, including pharmacological perturbations.
On September 14, 2014, Noetic announced that it has been selected for the second cohort of the AWS Generative AI Accelerator, launched by Amazon Web Services Inc (AWS) to identify top early-stage startups that are using generative AI to solve complex challenges and help them scale and grow. Participants will access AWS credits, mentorship and learning resources to further their use of AI and ML technologies and grow their businesses.
On August 30, 2024, AI-based Noetik closed on an oversubscribed $40M series A. The company plans to use the money to expand its atlas of human cancer biology with its in vivo CRISPR platform to advance a pipeline of cancer therapeutics to the clinic.