TechBio News: 1st part 👾
TechBio News: 1st part 👾
Revolutionizing Drug Development
Top Generative AI Drug Discoveries Companies By eWeek
On September 27, 2024, the Top 10 Generative AI Companies for Healthcare, Pharmaceuticals and Life Sciences by eWeek were:
🔶 Hippocratic AI (2022) is offering a foundation model and comprehensive resources for managing patient care and relationships. Most recently, Hippocratic AI has received funding from and started a partnership with NVIDIA. Hippocratic A.I. is First Safety Focused LLM for Healthcare.
🔶 Paige AI (2017), a global leader in end-to-end digital pathology solutions and clinical AI with the first Large Foundation Model, is using over one billion images from half a million pathology slides across multiple cancer types and is developing with Microsoft a new AI model that is orders-of-magnitude larger than any other image-based AI model existing today configured with billions of parameters. Paige Announces Collaboration with Microsoft to Build the World’s Largest Image-Based AI Model to Fight Cancer.
🔶 Iambic Therapeutics (2019), previously known as Entos, is developing physics-based AI algorithms to drive a high-throughput experimental platform, converting new molecular designs to new biological insights each week with: NeuralPLexer, OrbNet, PropANE and Magnet. In the research partnership announced this week with Lundbeck (FRA: LDBB), Iambic will use its AI drug discovery platform to accelerate research into neurological disease (migraine).
🔶 Insilico Medicine (2014) combines genomics, big data analysis and DL for in silico drug discovery. Insilico just Reported Positive Phase IIa Results for ISM001-055, a Novel First-in-Class Drug Treatment for Idiopathic Pulmonary Fibrosis (IPF) Designed Using Generative AI.
🔶 Etcembly (2020) is a company that is improving T-cell receptor immunotherapies with its ML platform, EMLy. The platform sifts through complex TCR patterns and datasets to discover and identify personalized TCR therapeutic options for patients. Etcembly just Launched Groundbreaking Research Study Searching for Cancer Cures in Survivors.
🔶 Biomatter (previously called Biomatter Designs) is a synthetic biology company founded in 2018 in Vilnius, Lithuania that leverages generative AI to create synthetic biologic materials, specifically new proteins and enzymes.
On August 6, 2024, Vilnius-based Biomatter raised €6.5M to unlock new horizons for protein design.
🔶 Activ Surgical (2017) uses intraoperative surgical intelligence to give surgeons real-time information and better visuals during surgery. On January 22, 2024, Activ Surgical Announced Completion of First International Procedure Using Its ActivSight™ Intelligent Light.
🔶 Kaliber Labs (2015) focuses on developing AI-powered surgical software for arthroscopic surgery needs.
🔶 Osmo, founded in 2023 as a spinout from Google Research, uses ML and has created a map of odors and scents to help computers predict how something smells based on its molecular structure. From there, the company has begun working on “teleporting scent” and generating artificial smells. AI Startup Osmo Tackles Scent Recognition in Health and Wellness.
🔶 Aqemia (2019) is an in silico drug discovery start-up using quantum physics and AI to transform the drug discovery process. The company started in France in 2019, as a deeptech spin-off from École normale supérieure and has built an innovation engine it calls the Aqemia’s Launchpad. Partner Spotlight: AQEMIA and Sanofi (EPA: SAN) Harness Generative AI and Deep Physics to Power R&D.
Sravathi AI
On September 29, 2024, 20/15 Visioneers Partners (a virtual R&D management consultancy) with Sravathi AI to Launch AI-Driven Drug Discovery Solutions in North America.
Sravathi AI Technology Private Limited is an India based AI startup located in Bangalore. Sravathi AI is focused on creating, discovering and developing innovative advanced pharma and chemical products.
Sravathi platform employs DL generative AI, computational chemistry and molecular modeling to streamline the identification and optimization of small molecules. The platform’s capabilities include in-silico drug discovery, with features such as property prediction, advanced molecular dynamics methods, and hit-to-lead optimization. In addition, its in-silico chemistry tools offer predictions for synthesis routes, impurities, toxicity and yield, providing a comprehensive solution for drug discovery and development.
Phare Bio
On September 27, 2024, Phare Bio received ARPA-H funds for AI drug discovery platform. Phare Bio, in collaboration with MIT’s Collins Lab and Harvard’s Wyss Institute, has received $27M from the Advanced Research Projects Agency for Health (ARPA-H) to advance its AI-powered drug discovery platform and develop new antibiotic classes. The funding will also support the progression of 15 new AI-generated preclinical antibiotic candidates.
Phare Bio (2020, US) is a social venture using novel AI and DL to tackle the world’s most urgent threats, like the aggressive evolution of antibiotic-resistant bacteria and a dwindling antibiotic discovery pipeline that have resulted in an antimicrobial resistance (AMR) crisis. Phare has integrated world-class expertise and decades of experience in AI, bioengineering and pharmaceutical development to rapidly discover and develop novel classes of antibiotics that target urgent threats like Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae. This unique and self-sustaining approach will enable them to outpace the emergence and global dissemination of antibiotic resistance. Phare Bio (a public charity located in Boston, MA) has partnered with the Collins Lab at MIT and the Broad Institute on its AI/DL platform for antibiotic discovery work.
Aitia
On September 26, 2024, Orion and Aitia partnered for AI-driven oncology drug discovery. In particular, the Finnish pharmaceutical company Orion and Aitia will leverage the Digital Twins technology of Aitia along with Orion’s (HEL: ORNBV) extensive pre-clinical and clinical expertise to discover and validate new drug targets. Aitia is entitled to receive milestone payments exceeding $10M per drug target.
Aitia Bio (ex GNS Healthcare) uses its Reverse Engineering and Forward Simulation (REFS) or Gemini Digital Twins, namely a causal AI and simulation platform, to analyze RWD and clinical trial data to model patient responses to treatments in silico and has worked with biopharma companies, including Amgen, BMS, Celgene, Johnson & Johnson and Novartis.
Gemini Digital Twins is combining multi-omics and clinical patient data by using Aitia’s patented causal AI and simulation technology, and can link patients’ characteristics to diverse drug treatments, in order to reveal complex genetic and molecular mechanisms and pathways driving clinical outcomes. For now, Aitia is advancing drug discovery programs in multiple myeloma, prostate cancer, Alzheimer’s Disease, Parkinson’s Disease and Huntington’s Disease.
University of Texas
On September 26, 2024, an Innovative AI from The University of Texas at Austin Revolutionized Drug Discovery was presented. In a significant leap for medicine and biotechnology, The University of Texas at Austin has unveiled an AI model capable of crafting proteins for new drugs and vaccines, known as EvoRank.
Evolutionary Ranking (EvoRank), is a training objective that incorporates evolutionary information derived from multiple sequence alignments (MSAs) to learn more diverse protein representations (AI Trained on Evolution’s Playbook Develops Proteins That Spur Drug and Scientific Discovery). EvoRank corresponds to ranking amino-acid likelihoods in the probability distribution induced by an MSA. This objective forces models to learn the underlying evolutionary dynamics of a protein. Across a variety of phenotypes and datasets, EvoRank has led to dramatic improvements in zero-shot performance and can compete with models fine-tuned on experimental data. This is particularly important in protein engineering, where it is expensive to obtain data for fine-tuning.
Four years after launching a remote-controlled robotic laboratory in San Diego, Eli Lilly (NYSE: LLY) is shipping the operation overseas by selling a majority of the Life Sciences Studio laboratory to Arctoris, a contract research organization with headquarters in Oxford, England and Boston.
Immunai
On September 26, 2024, Immunai and AstraZeneca announced a $18 Million AI Collaboration to Transform Cancer Drug Development. This partnership aims to enhance the development of oncology therapies through advanced data analysis. The collaboration will leverage Immunai’s proprietary technologies, including its immune cell atlas, AMICA, and the Immunodynamics Engine (IDE). As a result, AstraZeneca (LON: AZN) will utilize Immunai’s platform to inform clinical decision-making in its oncology trials.
Immunai is building an AI model of the immune system to facilitate the development of next-generation immunomodulatory therapeutics by combining immunomics and ML. Immunai’s rich clinico-genomic data assets are harmonized in AMICA™, the Annotated Multi-Omic Immune Cell Atlas. Fed by massive scale curated public -omics data and proprietary cohorts and experiments, AMICA™ covers 10s of millions of cells across hundreds of disease settings and is growing rapidly.
Founded in December 2018 and with a global team that spans New York City, Tel Aviv, Prague and Zurich, in March 2021 Immunai acquired Dropprint Genomics, a Y-combinator backed, single cell genomics software company based in San Francisco. Dropprint’s database of immune cells further expanded AMICA.
In July 2021, Immunai made the transformational acquisition of NEBION, a world leader in biocuration and data integration. NEBION has structured hundreds of thousands of samples and millions of cells across thousands of public studies under a unified clinical ontology, all powered by bespoke expert curation. This data has supercharged AMICA’s growth and expanded their target discovery efforts into a wide range of inflammatory and oncological settings.
After the acquisition, Nebion’s main product GENEVESTIGATOR that curates public and private transcriptomics data continues to be developed and commercialized. GENEVESTIGATOR, that has been over 10+ years in development, has the following key applications for curated gene expression data:
✳️ Effective discovery through compendium-wide analysis
✳️ Unbiased data-driven decision making
✳️ Straightforward prioritization and validation of targets and biomarkers
✳️ Innovative drug repurposing and repositioning
✳️ Convenient identification of relevant experimental model systems
✳️ Reliable prediction of side effects, and
✳️ Robust ML through clean data.
TVM Capital Healthcare invests in Human Longevity to fund international growth.
Human Longevity co-founder and chief scientific adviser Dr Craig Venter said:
“TVM Capital Healthcare’s investment enables us to strengthen our position globally as the most data-backed longevity practice, as well as establishes our foothold in markets, like Saudi Arabia and South-East Asia, that see the potential of our approach in preventive medicine and the huge impact it will have on changing cost of medicine.”
Cresset
On September 26, 2024, AI-driven drug discovery: insights from Cresset were highlighted. In this in-depth Q&A, Mutlu Dogruel, Vice President of AI at Cresset shares his insights surrounding chatbots, retrieval augmented generation and AI hallucinations, to open up new possibilities for innovation in pharmaceutical research.
Cresset delivers software solutions and contract research expertise enabling companies around the world to accelerate their small molecule discovery processes efficiently and effectively.
ReSync
On September 25, 2024, ReSync Bio Launched to Automate Data and Operations in Drug Discovery. ReSync announced a round of pre-seed funding from Caffeinated Capital, Atria Ventures and Ramsey Homsany, co-founder of Octant Bio. The company will use the funds to make key hires and commercialize their platform, which is now available for use by companies and academics.
ReSync Bio coordinates labs, data and AI models on one platform for integrated preclinical R&D. In order to properly leverage advancements in AI for drug discovery, teams need better tools to manage their data, ML models and experimental workflows. With ReSync, teams of all sizes (from academic groups and startups to biotechs and pharma) can focus on the most important part of their jobs: scientific advancement.
ReSync’s vision is to empower pharmaceutical and biotechnology companies to:
(from Can We Bring Drug Discovery Back to the Future?)
✳️ Make efficient decisions in the hybrid and virtual lab environment: Onboarding a new CRO shouldn’t require weeks of process definition and back-and-forth. ReSync natively tracks requests and fulfillment, and can provide templates for a variety of assay data types.
✳️ Adopt new technologies without overhead: They aim to supercharge biotech teams by providing a centralized data solution, allowing one-click integrations of homegrown models and benchmarks of open source and academic research.
✳️ Enhance collaboration and data security: ReSync’s platform is designed to facilitate seamless collaboration between internal teams and external partners while maintaining strict control over data access and intellectual property protection.
AI Model
On September 25, 2024, an AI Model Identified Potential Treatments for Thousands of Rare Diseases. A new AI model developed by scientists at Harvard Medical School, named TxGNN, can identify potential treatments from existing drugs for over 17,000 diseases, many of which currently have no approved therapies.
TxGNN represents a significant advancement in AI-driven drug discovery, particularly for rare diseases:
✳️ It is the first AI model developed specifically for identifying drug candidates for rare and untreated diseases.
✳️ It can handle the largest number of diseases (over 17,000) of any single AI model to date.
✳️ The tool is nearly 50% better at identifying drug candidates compared to leading AI models for drug repurposing.
✳️ It is 35% more accurate in predicting drug contraindications.
TxGNN was trained on vast amounts of data, including DNA information, cell signaling, gene activity levels and clinical notes.
Algorae Pharmaceuticals
On September 25, 2024, Algorae Pharmaceuticals launched AI-powered platform to generate novel drug candidates. Algorae Pharmaceuticals (ASX: 1AI) launched Version 1.0 of its biopharmaceutical platform AlgoraeOS after construction at the University of New South Wales. The AlgoraeOS platform aggregates medical and scientific data on over 5,000 known drugs and molecules in over 150 human cell types. The platform uses AI systems to predict fixed-dose combination (FDC) drugs that the company says it will either take to clinical trials itself or do so in collaboration with partners, potentially big pharma.
Algorae is a clinical-stage pharmaceutical company developing transformative solutions for significant undermet medical needs in the community. Right now is working on: AI-116 (a novel combination drug candidate made up of cannabidiol, CBD, and an off-patent pharmaceutical ingredient, a potential treatment for dementia, including Alzheimer’s disease), AI-168 (a novel combination drug candidate made up of a cannabinoid and an off-patent pharmaceutical ingredient, a potential treatment for cardiovascular disease, including hypertension) and NTCELL (an alginate coated capsule product containing clusters of neonatal porcine choroid plexus cells that are injected into the damaged site within the brain to target the treatment of Parkinson’s disease).
On October 25, 2023, Algorae Pharmaceuticals entered an agreement with the University of New South Wales (UNSW) to advance the development of its proprietary AI platform for drug discovery. The platform, known as Algorae Operating System, or AlgoraeOS, will build on an AI model already developed by the university’s data specialists and trained for pharmaceutical prediction.
AlgoraeOS is a closed-loop platform, to evaluate drugs and molecules for repositioning and combining into novel drug candidates aimed at patient cohorts experiencing significant unmet medical need. Moreover, the platform will interpret pre-clinical, clinical, chemical and biological data sets at an enormous scale to provide predictive insights into Algorae’s pipeline of prospective drug candidates.
XtalPi
On September 24, 2024, XtalPi Launched Computational Chemistry Software for Drug Discovery: XMolGen and XFEP. XFEP and XMolGen, are two proprietary software products designed to accelerate and enhance the efficiency of drug discovery. Scientists can generate diverse compound libraries using XMolGen's generative and predictive AI modules, and subsequently assess the potency of these compounds through physics-based ligand binding affinity predictions with XFEP, unlocking faster pathways to discovering novel therapeutics by efficiently tapping into diverse, unexplored chemical spaces. XFEP’s Applications are: Comprehensive Ligand Binding Prediction (Noncovalent, Covalent, Peptide, Macrocyclic Ligands, PROTAC) and Wide Drug Discovery Stage Application (Fragment Evaluation, Hit-to-lead, Lead Identification, Lead, Optimization). XMolGen’s Applications are: De-novo Molecular Generation, Focused-Library Generation and Virtual Screening
Xtalpi (QuantumPharm, HKG: 2228), an AI-powered drug discovery company based in China, is offering a closed loop of AI and quantum physics algorithms working in sync with the data factory of large-scale robotics experiments. In particular, XtalPi’s superior AI algorithms (and so far more than 200+) combined with physics-based methods and XtalPi’s advanced automation robotics can accelerate small molecule discovery, macro-molecular discovery, amplified chemical synthesis and solid state formulation.
Founded by a group of quantum physicists at MIT, XtalPi is a quantum physics-based, AI-powered drug discovery company. Through its Intelligent Digital Drug Discovery and Development (ID4) platform—incorporating QM, AI and high-performance cloud computing algorithms—at XtalPi they can predict with high precision physiochemical and pharmaceutical properties of small-molecule drug candidates, as well as their crystal structures, enabling successful drug discovery.
Xaira Therapeutics
On September 23, 2024, Xaira Therapeutics selected OCI to accelerate its AI drug discovery and development initiatives. Xaira Therapeutics is now using Oracle Cloud Infrastructure (OCI) to accelerate its mission to reimagine the way medicines are discovered and developed through the end-to-end application of emerging AI technologies. Xaira is already operational with industry-leading GPU capacity, powered by OCI.
Xaira Therapeutics is an integrated biotechnology company driving advances in AI to learn the language of life and transform how we treat disease. The company seeks to rethink the drug discovery and development process from end-to-end by bringing together leading talent across three core areas: ML research to better understand biology, expansive data generation to power new models and robust therapeutic product development to treat disease. Xaira is headquartered in the San Francisco Bay Area.
Incubated by ARCH Venture Partners and Foresite Labs, Xaira Therapeutics emerged from stealth in April 2024 with $1 billion in committed capital led by ARCH Venture Partners and Foresite Capital, with additional investment from F-Prime Capital, New Enterprise Associates (NEA), Sequoia Capital, LUX Speed Capital, Lightspeed, Menlo Ventures, Two Sigma Ventures, SV Angel and others.
AI can hunt for hidden clues to new drugs in published papers.
Researchers at FRONTEO are using natural language processing, a form of artificial intelligence, to search for new drugs from information in the published research literature.
FRONTEO Inc, an AI-solutions company, with its headquarters in Tokyo, has developed a natural language processing (NLP) model that adds a critical parameter—context—to the AI-powered analysis of research literature.
FRONTEO’s flagship AI engine, KIBIT, uses the distributional hypothesis to analyze word relationships in written texts.
Toyoshiba is leading the initiative to explore KIBIT’s use in drug discovery.
Oxford Drug Design
On September 20, 2024, Dr Alan D. Roth, CEO of Oxford Drug Design, explained how his AI drug discovery company has completed the first in vivo validation in its potential first-in-class approach against multiple tumors (Initial in vivo validation of novel cancer therapeutics using AI). In particular, a 28-day mouse trial showed clear efficacy as well as dose response, with rapid advances enabled by the company’s dual-competence discovery platform which integrates generative AI capabilities with tRNA synthetase expertise.
Oxford Drug Design, is an advanced spinout from Oxford University, an innovative biotechnology company discovering and developing novel therapeutics supported by pioneering computational methods. Based on the unique integration of their dual core competences in aminoacyl-tRNA synthetase enzymes and distinctive AI/ML methods, their pipeline expansion is focused on oncology. This distinctive drug discovery platform has been validated by the rapid discovery of novel therapeutic candidates with highly innovative chemical scaffolds and modes of action.
Rakovina Therapeutics and Variational AI
On September 17, 2024, Rakovina Therapeutics and Variational AI Announced a Drug Discovery Collaboration to jointly research DNA-damage response kinase targets to identify and develop novel small-molecule therapies against DNA-damage response (DDR) targets for the treatment of cancer.
Rakovina Therapeutics (TSX.V: RKV) Vancouver, Canada is using cutting edge Deep Docking™ AI to target DNA-damage response (DDR) mechanisms and create innovative precision medicines with the potential to improve patient outcomes across multiple tumor types. DDR is a collection of processes that identify and correct DNA damage in our cells millions of times every day, and many cancers harbor a defect in natural DDR mechanisms.
Variational AI in Vancouver (developer of the Enki™ platform) leverages a powerful new form of ML known as generative AI to free scientists from reliance on screening and libraries (both experimental and virtual) and to eventually generate de novo molecules with all the optimized properties, in order to discover efficacious, safe and synthesizable small molecule therapeutics in a fraction of the time and cost.
Under the terms of the agreement Rakovina Therapeutics has been granted an exclusive right to compounds generated by the Enki™ platform against the selected target product profiles and an option to license validated drug candidates for further development. Variational AI will employ the EnkiTM platform to identify novel inhibitors of specific DDR kinase targets selected by Rakovina Therapeutics. Rakovina Therapeutics will synthesize and evaluate the viability of these drug candidates as potential cancer therapies in its laboratories at the University of British Columbia.
Google Cloud
On September 16, 2024, Ginkgo and Google Cloud Teamed Up to Supercharge Drug Development with New Protein LLM.
Ginkgo Bioworks Holdings, Inc (NYSE: DNA), a leader in cell programming and biosecurity, has two innovative tools designed from its last year partnership with Google Cloud:
✳️ The first is a groundbreaking protein large language model (LLM) developed in collaboration with Google Cloud Consulting, to give both individual researchers and enterprise companies access to insights derived from Ginkgo’s proprietary data, empowering them to advance their drug discovery efforts.
✳️ The second offering is Ginkgo’s new model API, which brings sophisticated biological AI models directly to ML scientists. The API is now publicly available on Ginkgo’s website, while the protein-based LLM will soon be accessible via Google Cloud’s Vertex AI Model Garden.
Chai Discovery
On September 11, 2024, OpenAI-backed drug discovery startup Chai Discovery introduced a new AI model Chai-1. Chai-1, is a new multi-modal foundation model for molecular structure prediction that performs at the state-of-the-art across a variety of tasks relevant to drug discovery, enabling unified prediction of proteins, small molecules, DNA, RNA, covalent modifications and more. The model is available for free via a web interface, including for commercial applications such as drug discovery. Chai is also releasing the model weights and inference code as a software library for non-commercial use.
Chai Discovery, is building AI foundation models to predict and reprogram the interactions between biochemical molecules, the fundamental building blocks of life. Chai Discovery is a startup founded six months ago and has raised nearly $30M from heavyweights Thrive Capital and OpenAI to bring AI to drug discovery.
ZipBio
On September 9, 2024, ZipBio Raised $4M in seed funding led by NFX with participation by MoreVC to Fuel its Generative-AI Compression Platform and Pipeline of Blockbuster Potential Drugs. ZipBio’s COMPACT platform uses generative AI to shrink the size of novel therapies to increase their likelihood of success.
ZipBio, a startup developing a generative AI platform for gene and protein compression, is building a proprietary platform (COMPACT platform) to compress complex biological structures into smaller, more efficient de novo-designed proteins that retain full functionality, optimizing delivery and therapeutic effectiveness for intractable and hard-to-treat diseases. The input to the platform is a set of disease causing/modifying targets that cannot be targeted due to size limitation on the potential therapeutic molecule.
Genetic Leap
On September 5, 2024, Eli Lilly jumped deeper into AI with $409M Genetic Leap deal. The news of the deal with the RNA specialist Genetic Leap came after Eli Lilly (NYSE: LLY) pushed deeper into RNA by opening a $700M nucleic acid R&D center in Boston’s Seaport neighborhood, back in 2022. Now Big Pharma has entered into a research pact that will see Genetic Leap use its RNA-targeted AI platform to generate genetic drug candidates against selected targets. Lilly will pick targets in high-priority areas and Genetic Leap will find oligonucleotide drugs against the targets. The pact is worth up to $409M in upfront and milestone payments.
Genetic Leap is innovating at the cutting edge of AI and RNA genetic medicine to redefine drug development and more quickly address the health needs of millions of people. The Genetic Leap AI stack consists of Bergspitze and Franklin that together constitute Genetic Intelligence, and are used for genetically-defined target discovery for diseases with no tractable target.
✳️ Bergspitze tames the noise and small sample challenges of the whole genome to pinpoint genetic positions causal of disease, no matter their location throughout the full 100% of the genome.
✳️ Franklin deep-traces causal genetic variants through biomolecular networks in granular, rigorous analyses that provide a coherent etiology model for the disease and affirm targets to modulate for a cure. Franklin is an AI representation of the body’s universe.
Moreover, Orisha designs molecules to drug a target’s RNA transcript effectively and efficiently. Orisha has two sub-modules:
✳️ Orisha-SM drugs the structure of RNA using small molecules in three stages: 1) identify the best regions with unique structure on the RNA, 2) predict the structure of the selected regions and 3) dock small molecules against the predicted structure.
✳️ Orisha-oligo drugs the sequence of RNA using oligonucleotides in two stages: 1) identify the most accessible yet unique region on the RNA and 2) design an ASO sequence to drug it.
Finally, Lea confirms experimentally the targets and drug candidates from the AI layers using cell assays and animal models that are relevant to both disease etiology and human biology.
Apart from Lilly, Genetic Leap has a research collaboration agreement also with Astellas Pharma, Inc (TYO: 4503) to develop novel RNA-targeted small molecule therapeutic candidates against an undisclosed oncology target.
Syntekabio
On September 3, 2024, Syntekabio and Enamine partnered for AI-based drug development. Syntekabio has partnered with Ukraine-based global compound supplier Enamine for supply, synthesis of compounds and synthetic drug development. Under the Memorandum of Understanding (MOU) signed by the companies, the alliance will leverage an extensive synthetic compound library provided by Enamine to support drug candidate discovery services through Syntekabio’s AI platform, DeepMatcher. The companies will work together at the AI Bio Supercomputer Center in Daejeon.
Syntekabio (KOSDAQ: 226330) (2009, South Korea) is a global partner for AI drug discovery and repurposing drugs (AI Drug Repurposing: source, source), using DeepMatcher, an AI drug development platform that combines new drug development technology and big data (such as biomarkers for individual cancer drug screening and disease susceptibility by immunotyping, pharmacogenomic typing, and predicting multi-omics information-based drug adverse effects, etc).
So far, the company has functionally segmented the entire process of AI drug development and clinical genomics analysis into step-by-step modules and has created the "Cloud-SaaS” service applying Cloud supercomputing automation processes.
Syntekabio's AI can access over 10 billion known compounds as well as 1,400 in vitro/in vivo compatible drug targets covering over 70% of human diseases. This technology is powered by Syntekabio's AI Bio-Supercom Center, which houses an immense infrastructure of 5,000 servers (as of Q1 2024), 40,000 CPU cores and 2,500 GPUs fueling the company's algorithms. The ABS Center, a crucial resource for drug development, integrating supercomputing and AI systems to enable highly precise simulations and modeling in drug development, opened in October 2023 and currently is producing AI drug candidate material on a factory-wide scale.
For more about Syntekabio:
Lucid Genomics
On September 3, 2024, Lucid Genomics emerged with AI platform that unravels the secrets of the ‘dark genome’. The Berlin based Lucid Genomics secured €1.3M in pre-seed funding to advance its AI-driven platform focused on diagnostics and biomarker identification. The Berlin-based company, a spin-off from the Max Planck Institute for Molecular Genetics and Berlin’s Charité University Hospital, aims to enhance our ability to analyze and understand genomic data, supporting more precise drug discovery and diagnostics.
Lucid Genomics created an AI-based algorithm capable of filtering noisy datasets from short-reads data. This method allows users to mine 100% of the DNA dataset at a very low cost. Detected mutations are:
Coding and non-coding variants, SNVs, Indels and Structural Variants, RNA-seq analysis and Methylation analysis. On top of that, a second ML method was created to score DNA mutations irrespective of their location in the genome. This ML delivers a short list of candidate variants to answer their questions taking into account the epigenetic information.
Lucid claims its ML algorithms uncover patterns in the dark genome to identify genetic variations with greater accuracy, extracting new insights from these previously neglected areas. The company’s platform is designed to process whole genome datasets, offering solutions for the healthcare and pharmaceutical industries via a Software-as-a-Service (SaaS) model.
Made-at-Mac: A Scientist heads a new AI drug discovery start-up in search of antibiotics, anticancer medicines, he is also an assistant professor at McMaster University, a member of the Michael G. DeGroote Institute for Infectious Disease Research (IIDR) and the founder of Stoked Bio, the new biotech start-up company.
Noetik
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.
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.