TechBio News ?? (July 2024)
MetaphysicalCells: A newsletter about Science, Technology and AI Drug Discovery

TechBio News ?? (July 2024)

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Latest News ??

?? Insilico Medicine completes patient enrollment in its Phase IIa Study in China investigating INS018_055 for Idiopathic Pulmonary Fibrosis (IPF)

  • The primary objective is to evaluate the safety and tolerability of INS018_055 orally administered for up to 12 weeks in adult subjects with IPF compared to placebo. In addition, Insilico is preparing a Phase IIb proof-of-concept study to be initiated in 2025 to explore the efficacy and further safety of INS018_055.

?? AI Isn’t the Magic Bullet to Simplify Drug Discovery

  • Wet-lab biology and translational models are key to confirming AI-derived findings.

?? Formation Bio raises $372M to boost drug development with AI

  • Formation Bio, a startup focused on applying AI to drug development with backing from OpenAI CEO Sam Altman, it raised $372M in a Series D funding round led by Andreessen Horowitz with participation from drug maker Sanofi, Sequoia, Thrive, Emerson Collective, Lachy Groom, SV Angel Growth and FPV Ventures.

?? AI In Drug Discovery Market Size to Expand US$ 11.93 Bn by 2033

Report Highlights:

  • North America region has accounted for a market share of around 56.18% in 2023.
  • The APAC market is expected to grow at a CAGR of 21.1% from 2024 to 2033.
  • By therapeutic area, the oncology segment has accounted for a market share of 21% in 2023.
  • Based on application, the drug optimization and repurposing segment has captured market share of 51% in 2023.
  • The US AI in drug discovery market size was valued at USD 670M in 2023.

?? Iktos acquires Synsight , a life sciences technology company specializing in protein-protein and RNA-protein interactions-targeted drug discovery

  • Synsight provides Iktos with an exclusive worldwide license to INSERM’s patented technology enabling high performance AI-driven in cellulo screening of modulators of protein-protein and RNA-protein interactions

?? Folding the human proteome using BioNeMo : A fused dataset of structural models for machine learning purposes

  • An extensive dataset of predicted protein structures for 42,042 distinct human proteins, including splicing variants, derived from the UniProt reference proteome UP000005640. To ensure high quality and comparability, the dataset was generated by combining state-of-the-art modeling-tools AlphaFold 2, OpenFold and ESMFold, provided within NVIDIA’s BioNeMo platform, as well as homology modeling using Innophore’s CavitomiX platform

?? Machine learning-aided generative molecular design

  • A comprehensive overview of the current state of the art in molecular design using ML models as well as important design decisions, such as the choice of molecular representations, generative methods and optimization strategies.

?? Simulating 500 million years of evolution with a language model

  • EvolutionaryScale.ai , an AI-for-proteomics startup that just came out of stealth, announced ESM3 a 98B-parameter generative LLM for "programming biology."
  • Using ESM3 and a simulated evolutionary process, they have produced a new type GFP (Green Fluorescent Protein) different from anything found in nature.

?? Startup Combines AI with Ancient Remedies for Drug Discovery

?? NVIDIA and Recursion’s candid conversation on AI’s next big leap in drug discovery

  • Supercomputing meets biology

?? Lantern Pharma Achieves Key Milestone Towards Development of Molecular Diagnostic for use in Oncology Clinical Trials for Patient Selection and Stratification with Drug Candidate LP-184

?? France’s Bioptimus Releases AI Model for Disease Diagnosis

?? IMGAIA : Insilico Medicine Generative AI Action. Event by Insilico Medicine

?? Exscientia extends AWS partnership to boost AI drug discovery platform

?? Backed by Nvidia and Pfizer , Israeli AI medical startup raises $80m in fresh capital

  • Tel Aviv-based CytoReason, which uses machine learning to build computational models of human diseases to speed up treatment discoveries, plans to open a US office later this year

?? Living Cell Technologies Unveils AI Drug Discovery Platform

  • Living Cell Technologies Ltd. is set to launch its AlgoraeOS AI platform, which will predict drug combinations for diseases by analyzing vast medical data.

?? The Bioptimus team just released H-optimus-0

  • H-optimus-0 is the world’s largest open-source AI foundation model for pathology that achieves SOTA performances in many important downstream tasks

?? OpenAI and Los Alamos National Laboratory announce bioscience research partnership

  • OpenAI and Los Alamos National Laboratory are developing evaluations to understand how multimodal AI models can be used safely by scientists in laboratory settings

?? Singapore's BluMaiden Secures Major Funds for AI Drug Discovery Expansion

  • Utilizing AI-guided computational genetics and chemistry, BluMaiden aims to explore the extensive chemical space within the human body to develop new medicines.

?? Insilico Medicine launches AI assistant for drafting medical research papers

  • Named DORA, the manuscript helper taps multiple AI and large language models to support the drafting of academic papers and case studies, in addition to applications for grants and patents.

?? SilicoGenesis In Silico Genesis Ltd

SilicoGenesis (2019, Belgium) is developing an AI-enabled in silico antibody engineering platform, providing state-of-the-art AI/ML technology integrated into a scalable cloud-based platform for: Precise 3D modeling of protein structures, Accurate prediction of paratope and epitope residues, Characterization and modeling of protein-protein interactions, Enhancement of binding affinity and mutagenesis studies, Cross-species reactivity analysis, Expert humanization of antibody candidates and Rigorous assessment of developability liabilities. Their cloud-based software platform for biologics design, discovery and optimization is called Eve.

They also offer Protkit , an Open Source Python library that can be used for a variety of tasks in computational biology and bioinformatics, focusing on structural bioinformatics, protein engineering and ML. Protkit allows you to download protein structures and sequences from a variety of trusted sources, such as RCSB PDB, Uniprot and SAbDab.

In particular, Protkit can be used for a variety of tasks in computational biology, such as reading and writing from popular data file formats, downloading data from popular protein databases, data structures for representing proteins and molecules, detecting and fixing anomalies in structures, calculating properties of proteins, running various external tools, featurization for ML, etc.

The company was founded by Lionel Bisschoff and Fred Senekal in 2021 in Johannesburg, South Africa and Ian Wilkinson is the scientific advisor. Ian is a protein biochemist with an interest in protein and antibody engineering that has previously acted as the CSO of Absolute Antibody (for antibody sequencing, engineering and recombinant manufacturing) and mAbsolve with a Fc silencing technology (which he co-founded) and is the founder of mAbvice consulting services.

Shortly after, SilicoGenesis’ headquarters were established in Leuven, Belgium. In 2022, their first academic collaboration was established on a project involving CART-T cell therapy, utilizing the Eve platform. In the first quarter of 2023, they begun collaborations with partners from around the globe including one of the largest pharmas based in Europe, on an affinity maturation project for a difficult cytokine target:

  • ?? Given the sequence of the antibody candidate, they predicted its structure and PPI interaction with the target antigen. They successfully modeled the three-dimensional structure of the complex and used this highly accurate model to perform in silico saturation mutagenesis. They were able to correctly identify all of the top affinity-enhancing mutations in the CDR regions confirmed by in vitro saturation mutagenesis using ELISA and SPR.
  • ?? They performed rapid in silico affinity maturation of a lead candidate in less than a month.

Recently, SilicoGenesis began a collaboration with the Laboratory for Thrombosis Research (KU Leuven) and PharmAbs (KU Leuven Antibody Centre). The project involves in silico antibody engineering and optimization as well as in vitro and in vivo testing and validation. The goal of the project is to determine if the engineered lead molecule has improved developability characteristics and preserves binding affinity and species cross-reactivity.

?? FabricNano Limited FabricNano

FabricNano (2018) is a biotechnology company based in London with the mission to transform industrial chemical processes using cell-free biomanufacturing, with an advanced, flexible and easily-scalable biocatalyst platform. They develop and sell biocatalysts for high volume industrial applications, utilizing a data-driven approach for enzyme and Immobilization Engineering?. Their clients range from startups to international clients like Sumitomo Chemical Company (FabricNano and Sumitomo Chemical America partner to develop the next generation of cell-free bio-manufacturing ), Ginkgo Bioworks (Ginkgo Bioworks partners withFabricNano to unleash Immobilization Engineering? for a wide range of enzyme discovery projects ), ALMAC and many more.

The FabricNano process starts with novel Immobilization Engineering? for enzyme stabilization, followed by budget-conscious protein engineering and process engineering to reach the client’s targets for commercialization of the new biochemical production process.

In other words, FabricNano collects all the enzymatic components necessary for biomanufacturing and co-locates them on an artificial surface. The company has tried everything from a nano-wafer fabric made of DNA, to more industrially available materials such as common solid carriers, coffee grinds and even simple rocks (FabricNano is pioneering sustainable chemical production with cell-free biocatalysis ).?Once the enzymes are durable and stable they can be used to manufacture commodity chemicals like bio-plastics, bio-fuels and certain types of antibiotics that are made using enzymes. For example, the Epoxy E0001-0488-01 with Penicillin Acylase .

Furthermore, these biocatalysts ?? are what is known as “drop-in,” so they can just go into pre-existing industry equipment and know-how (such as packed bed or continuous stirred tank reactors).?

The company is backed by Atomico and Hoxton VC (as well as prominent angel investors) and has?raised a total funding of $22.6M over 2 rounds from 12 investors. Founder and CEO at FabricNano is Grant Aarons .

? cfdx

cfdx (2023, London, UK) is an AI neuroscience company, currently in stealth mode, co-founded by Hannah Thompson, PhD and Jonathan Wan .

cfdx aims to apply the liquid biopsy techniques used in early cancer detection to neurodegenerative diseases, enabling diagnosis decades before symptoms appear.

?? StoneWise (Beijing StoneWise Technology Co, Ltd) StoneWise

StoneWise (2018, Beijing, China) (望石智慧) utilizes AI to enable knowledge mining, molecule generation and property prediction allowing researchers to build knowledge graphs of scientific literature, predict molecular properties, design novel molecules and perform retro-synthetic analysis. StoneWise has set up an efficient and practical AI-based drug design platform, StoneMIND? (Master of Intelligent Novel Design), which provides a unified SaaS platform for information extraction, knowledge mining and molecular design. In particular:

  • ??? StoneMIND Collector (Information Extraction System): Is an AI enabled software tool capable of quickly extracting chemical structures from patent documents, literature and various pictures, and users can easily edit physical and chemical property data of the extracted structures. The obtained structural information and analysis results can be exported to various computer-readable formats at any time (SDF/MOL/SMILES/XLS/PNG).
  • ??? StoneMIND Designer (Molecular Design System): Is a multi-layer model for molecule design and optimization based on ligands, receptors and fragments, empowered by an intricate combination of AI, domain knowledge and a massive database. With the support of high-throughput screening of structures, is making it possible for researchers to discover quality molecules even faster.
  • ??? StoneMIND Inspirer: Is an auxiliary decision-making tool of SAR visualization analysis for R-group optimization. It aims to help researchers conduct statistical analysis of chemical and biological data, quickly carry out SAR research, and give reasonable suggestions on fragment alteration. It provides one-stop assistance for structural modification and alteration of small molecules, so as to bring molecular design into the era of rational design.
  • ??? KDD (Knowledge Discovery in Database): System of massive data annotation, relations optimization and analytic tools enable easier collection, categorization and archiving.

Founder and CEO of StoneWise is Zhou Jielong . In 2018, Zhou Jielong, a key force behind the evolution of Baidu’s search engine, established StoneWise to aid in the discovery of small-molecule drugs (AI drug discovery booms in China ). Zhou Jielong (Master Degree of Artificial Intelligence, Beijing Institute of Technology) was Baidu’s former Principal Architect, and was responsible for application of ML technologies into Baidu’s core business, including core page ranking, anti-spam, cloud-based voice search and image search algorithms. He led the team to re-frame Baidu’s search engine with ML algorithms, and made innovative efforts in a few AI fields, including AI system, AI expandability and AI robustness. In 2013, he led his team to successfully apply DL to search engines for the first time in the world.

In 2021, StoneWise completed its series B and series B+ funding rounds raising $100M combined.

? Recursion Pharmaceuticals Inc (NASDAQ: RXRX) Recursion

Recursion (2013, Utah US) is a leader in digital biology, and has built the world’s most advanced ultra-high throughput wet-lab and ML platform. Their ability to generate proprietary, high-dimensional, multi-modal and relatable datasets of human cellular biology at massive scale, and apply advanced ML approaches to reveal novel biological relationships, has resulted in a proven, target-agnostic drug-discovery engine. Recursion Pharmaceuticals Inc (RXRX) went public in April 2021.

Recursion Pharmaceutical has at its headquarters clusters of robots that treat millions of cells per week with drugs, stain them with six dyes and then take pictures to capture and quantify as many morphological features as they can. By pushing these data through a ML pipeline, they hope to find relationships that are invisible to the human and to tease out clusters of effects that can guide their drug discovery.?

? In?2020 , a strategic collaboration was announced that will leverage?Recursion’s purpose-built AI-guided drug discovery platform and Bayer’s small molecule compound library and deep scientific expertise to discover and develop new treatments for fibrotic diseases of the lung, kidney, heart and more. Under the terms of the agreement, the parties can initiate more than 10 programs with possible development and commercial milestone payments of more than $100M per program plus royalties on future sales. In addition to the $50M equity investment, Recursion will receive an upfront payment of $30M.

  • On November 10, 2023, Bayer and Recursion expanded their oncology research partnership and may launch up to seven oncology programmes.
  • Bayer will be the first beta-user of their LOWE LLM-orchestrated workflow software, which will be integrated across the collaboration and offer a more exploratory, and intuitive research environment for scientists on both sides.
  • LOWE is an LLM agent that represents the next evolution of the Recursion OS . LOWE supports drug discovery programs by orchestrating complex workflows. These workflows chain together a variety of steps and tools, from finding significant relationships within Recursion’s Maps of Biology and Chemistry to generating novel compounds and scheduling them for synthesis and experimentation. Through its natural language interface and interactive graphics, LOWE puts state-of-the-art AI tools into the hands of every drug discovery scientist at Recursion in a simple and scalable way.
  • Additional updates pertaining to the Bayer partnership include :

? On September 2020 , it was announced by the company an oversubscribed series D funding round of $239M. Recursion has raised a total of $665.4M.

? On December 7, 2021,?Recursion announced a transformational collaboration with Roche and Genentech, in order for Recursion to work with both Roche and Genentech's R&D units to leverage technology-enabled drug discovery through the Recursion Operating System (OS). Under the terms of the agreement, Recursion will receive an upfront payment of?$150M?while Roche and Genentech (combined) may initiate up to 40 programs, each of which, if successfully developed and commercialized, could yield more than?$300M?in development, commercialization and net sales milestones for Recursion, as well as tiered royalties on net sales.

  • On October 2, 2023, just over one and a half years into the exciting collaboration with Roche and Genentech, Recursion announced that they have reached the first milestone: after building fit-for-purpose oncology maps for their partner spanning whole-genome arrayed CRISPR knockouts and hundreds of thousands of small molecules, they have identified and validated the first hit series for this particular disease, and Roche has exercised the Small Molecule Validation Program Option.

? On June 12, 2023, Recursion acquired the two emerging Canadian AI drug-discovery firms: Cyclica and Valence . Subsequently, Recursion announced a collaboration and a $50M investment from NVIDIA. Then Recursion launched Valence Labs, formerly Valence Discovery, a company with roots at Mila and mentorship from Yoshua Bengio (a Canadian computer scientist, most noted for his work on AI networks and DL), dedicated to advancing DL in drug discovery, delivering impactful research and transformative technology and embracing open-source and open-science knowledge sharing with the ML community.

? On January 8, 2024, Nvidia Corp. (NVDA) doubled down on AI powered drug discovery and development, announcing an expanded partnerships with Amgen Inc (AMGN) and Recursion Pharmaceuticals Inc (Nvidia dives deeper into AI drug development with Amgen , Recursion partnerships ). Amgen’s subsidiary deCODE Genetics is building out a supercomputer to create genomics “foundation models”—models trained on massive datasets to tackle a variety of jobs—to fuel drug discovery. deCode will power its new genomics foundation models with Nvidia’s supercomputer and BioNeMo generative AI platform. Recursion is also joining the party and will be the first third-party addition to the BioNeMo platform, adding its Phenom-Beta program for wider use.

? On May 12, 2024, it was announced that NVIDIA bought $70M of shares in RXRX 1.64%↑ . Recursion Pharmaceuticals collaborates with NVIDIA to accelerate drug discovery using AI technology. Their newest supercomputer,?BioHive-2, powered by?504 NVIDIA H100 Tensor Core GPUs, delivers?2 exaflops of AI performance—nearly 5x faster than their previous system (Recursion Pharmaceuticals is at the forefront of AI-driven drug discovery! ).

  • Recursion’s BioHive-2 is the largest system in the pharmaceutical industry. It’s located at Recursion’s headquarters in Salt Lake City.

Recursion’s integrated Recursion Operating System creates a closed-loop system combining proprietary in-house data generation and advanced computational tools to generate novel insights to initiate or accelerate therapeutic programs. Afterwards, their in silico predictions are validated in their own wet laboratories, and repeated, creating a mutually reinforcing cycle of learning. So far, they have something like ~19 petabytes of proprietary high-dimensional data and the company has the following clinical trials :

  • REC-994 in phase 2 for
  • REC-2282 in phase 2 for
  • REC-4881 in phase 2 for
  • REC-3964 in phase 1 for
  • RBM39, a novel CDK12-adjacent target identified by the Recursion OS, for HR-Proficient Ovarian Cancers and Other Solid Tumors. As a result of their collaboration with Tempus, they are leveraging genomic data across all tumor types to identify clinical biomarkers for patient expansion.
  • Undisclosed Indication in Fibrosis (Target Epsilon) from the fibrosis collaboration with Bayer which is now entering initial investigational new drug (IND) enabling studies.

  • Dozens of internal and partner programs in early stages with the first LLM and causal model driven programs entering the Recursion pipeline .

?? Tierra Biosciences Tierra Biosciences

Tierra Biosciences (2015, US) is a synthetic biology company that accelerates the pace of discovery and enables the next generation of bio-based materials, with its AI-driven Tierra Protein Platform, that couples high-throughput protein manufacturing with the simplicity of e-commerce to make ordering custom proteins easier than ever before.

Advances in DNA synthesis, DNA sequencing and de novo protein design have made exploration of diverse sets of sequences easier. But the challenge has now moved to protein synthesis and the solution is the cell-free expression Tierra Protein Platform, where you can:

  • Input your digital protein sequences and get AI-driven computational insights into synthesis profiles and risks.
  • Then receive physical, testable proteins that have gone through extensive experimental validation and QA/QC. All through a single digital portal.
  • Tierra’s proprietary cell-free expression technology utilizes the components of a living cell, but not the cell itself, since engineering and manipulating cells can be a challenge.?Then by combining automation, computational analysis and high-throughput cell-free expression, is synthesizing proteins?from diverse sources.
  • By providing high throughput rapid protein synthesis from digital protein sequences, Tierra allows you to move quickly, efficiently, and cost-effectively to your downstream assays to screen and identify hits.
  • Finally, you can get your custom, purified μg- and mg-scale proteins in as little as 3 weeks.

Tierra’s technology was originally developed at Caltech. Co-founders are Zachary Sun and George Church , one of the living legends of modern genetics.

With applications in biopharma (Antibody engineering , Difficult-to-express proteins and Drug Targets ) and synthetic biology (Computationally designed proteins en masse , Protein engineering , Toxic Proteins , Pathway and metabolic engineering and Metagenomic Screening ), Tierra Biosciences raised in March 2024 a $11.4M series A to expand its designer protein-to-order platform.

Longevity ??♂?

?? Aging Intervention Foundation Aging Intervention Foundation

Aging Intervention Foundation has a mission to increase Healthspan and Lifespan, and to slow and ultimately reverse biological aging and age-related decline for more years of healthy living, utilizing the following modalities:

  • Gene therapy and AI for drug design and biomarker analysis
  • Plasma Therapies, therapeutic plasma exchange/removal of pro-aging factors and adding youth enhancing factors
  • Mitochondrial therapies
  • Yamanaka/OSK systemic therapy , reset the epigenome toward youth/cellular reprogramming
  • Personalized Microbiome therapies
  • NAD and NAD enhancement supplements, AlphaKetoglutarate (AKG), nutritional supplements and Kaufmann protocol, cognitive and life enhancement
  • Senolytics, Peptides, Exosomes, Engineered Reprogramming Extracellular Vesicles (VSELs) and Protein profile control
  • Aging Intervention Program System Therapies Metrics.

The Aging Intervention Foundation is run by Johnny Adams , that he is actively looking right now for exceptional people to create aging solutions, money to make it happen, grants for exceptional researchers, as well as to fund companies for equity and to partner with labs in the US and offshore working on TechBio Longevity. His supporters will get early access to longevity therapies, valuable information and money if they desire.

In his Scientific Advisory Board you can find “great minds” ?? like:

?? Longevity and TechBio

Headquartered in Toronto, Deep Genomics ?uses AI and ML to develop life saving drugs by combining DNA, biomarkers and cell machinery. Since its founding in 2015, Deep Genomics has built several predictive systems known as the AI Workbench, and has made billions of predictions across the entire human genome, for millions of genetic variants, and hundreds of millions of novel compounds. So far, the company has used its computational system to develop a database that provides predictions for more than 300 million genetic variations that could affect the genetic code.

Its proprietary AI platform, BigRNA, which is the world’s first RNA foundation model for RNA therapeutics, can predict tissue-specific RNA expression, splicing, microRNA sites and RNA binding protein specificity. BigRNA can uniquely discover a wide range of new biological mechanisms and RNA therapeutic candidates that would not be found using traditional approaches that measure only overall gene expression levels. In contrast, BigRNA is trained to predict RNA expression at sub-gene resolution, such as polyadenylation, exon skipping and intron retention (An RNA foundation model enables discovery of disease mechanisms and candidate therapeutics ).

Deep Genomics made headlines back in 2019 with discovering a novel target and a novel RNA therapeutics candidate, DG12P1, for the rare Wilson disease using its platform BigRNA, all within 18 months of initiating target discovery efforts (Deep Genomics Nominates Industry’s First AI-Discovered Therapeutic Candidate ). In particular,

  • Deep Genomics’ AI system scanned over 2,400 diseases and over 100,000 pathogenic mutations while searching for good drug development opportunities and was able to predict and confirm the precise disease-causing mechanism of the mutation Met645Arg. One of several genetic mutations that leads to loss of function of the ATP7B copper-binding protein, a genetic mutation that impairs the body’s ability to remove copper, and thereby identify a clear therapeutic target. The AI system was then used to identify 12 lead candidates out of thousands of potential compounds, taking into account in vitro efficacy and toxicity. In particular, TDG12P1 was designed to correct the exon skipping mechanism of Met645Arg and after tolerability experiments Deep Genomics declared it the ideal candidate to advance toward IND.

On June 12, 2024 , Deep Genomics announced the opening of its new office and lab facility in Cambridge, Massachusetts (the expansion of its Toronto office) and several key leadership hires. Deep Genomics raised so far a total of $180M to automate drug discovery.

Off course, it's not only Deep Genomics studying genetic variability. Regarding genomic instability (the high frequency of mutations), namely the first hallmark of aging. On July 11, 2024, the “Targeting chromosomal instability (CIN) in patients with cancer review was published, describing advances regarding our understanding of CIN from a translational perspective, highlighting both challenges and opportunities in the development of therapeutic interventions for patients with chromosomally unstable cancers:

  • CIN has long been recognized as a hallmark of aggressive human malignancies.
  • CIN drives cancer progression by generating genomic alterations such as chromosomal gains, losses and complex rearrangements. CIN can also drive the development of epigenetic abnormalities and chronic inflammation?that facilitate both metastatic dissemination and immune evasion.
  • Several novel treatment approaches include KIF18A inhibitors, p53-reactivating agents and PLK4 inhibitors, all of which are currently being tested in clinical trials.

On September 28 , 2021, Genomic Vision announced the launch of TeloSizer, for precise detection and quantitative measurement of telomere length (the 2nd hallmark of aging). The new TeloSizer service was built on Genomic Vision’s proprietary technology FiberSmart, of AI automation analysis, to?automatically detect, grab images and quantify telomere length on single DNA molecules.

Unfortunately, on November 17, 2023 Genomic Vision—a biotechnology company that develops products and services for the highly accurate characterization of genome modifications—announced that it decided to open a receivership procedure to protect the company and avoid bankruptcy.

Alzheimer’s disease (AD) is influenced by both genetic and brain epigenomic alterations and “Multiple array-based Epigenome-Wide Association Studies - EWASs" have identified robust brain methylation changes in AD. For this reason, a group of researchers developed EWASplusa computational method that uses a supervised ML strategy to extend EWAS coverage to the entire genome—finding genes near top EWASplus loci enriched for kinases and genes with evidence for physical interactions with known AD genes (A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer’s disease ). The epigenetic alterations—genes are turned on or off by changing the chemical structure (methylation) of DNA but not changing the DNA coding sequence—have been shown to be correlated with many aging diseases, including autoimmune disorders, neurological disorders as well as Huntington, Alzheimer’s, Parkinson’s diseases and schizophrenia, and is considered the 3rd hallmark of aging (The Hallmarks of Aging ).

The US health data firm TruDiagnostic is building out its epigenetic platform and testing services, which aim to provide the most accurate and insightful longevity analysis using information found in the epigenome. Its flagship testing product, TruAge, measures biological age using DNA methylation data, but the company also provides a wide range of aging-related metrics, from telomere length and immune cell measurements to current rate of aging, intrinsic and extrinsic age calculations and more (TruDiagnostic: a new level of epigenetic testing in longevity ).

The company went from zero to $80M within three and a half years in terms of revenue, and from one employee to hundreds within three-and-a-half years. In 2020, TruDiagnostic built its 20,000 square foot CLIA-certified and HIPAA-compliant lab in Lexington, Kentucky, with the aim of helping drive the fields of epigenetics and longevity-focused personalized medicine.

They are involved in the following clinical trials :

  • Doterra is conducting multiple studies to evaluate the impact of their essential oils. The first study with a product called On Guard, which is an essential oil blend to support the immune system.

  • A prospective, non-randomized 4 month study, containing 50-100 patients to evaluate Semaglutide’s Impact on epigenetic aging.
  • A prospective non-randomized study of 20-25 patients over age 40 to evaluate the effects Quercetin and Dasatinib have on healthy individuals over a 6-month period.
  • A study to compare multiple DNA methylation age indicators between a group of participants following the standard American diet to a group of participants who have followed the Nutritarian diet for at least five years
  • And many many many more.

In 2020, Astellas acquired the UK based Nanna Therapeutics ?for €80M to boost the development of anti-aging drugs. Through this deal, Astellas gained access to Nanna’s drug discovery technology—which focuses on drugs that target the mitochondria (the 4th hallmark of aging)—developing a treatment for a genetic syndrome called "mitochondrial encephalopathy, lactic acidosis and stroke-like episodes", or MELAS (caused by a change in one of several genes that help build mitochondria, cell structures that convert food into energy). Nanna’s microfluidics-based drug discovery technology was a big attraction for Astellas. Since with its high-throughput platform, Nanna can generate, screen and acquire data on billions of small molecules in parallel, producing drug candidates in a matter of months rather than the years it typically takes.

In a study that was published in 2022, a group of researchers screened 60 herbs derived from a book on Chinese traditional medicine, and have identified hesperetin (a structural analog of the sophricoside and genistein found in Sophora japonica), as a uniquely powerful Cisd2 activator (pro-longevity gene Cisd2). In fact, previous research has shown that Cisd2 expression is associated with longevity in mice (by aiding mitochondrial function) and that Cisd2 deficiency is associated with premature aging in mice (Hesperetin Upregulates Metabolism and Longevity in Mice ) .

  • In particular, Cisd2’s effects on mitochondria are due to its effects on calcium homeostasis and its deficiency causes problems in multiple organs, as mitochondria become overloaded with calcium ions. Hopefully, hesperetin clearly influences mitochondrial function in a way that leads to significant and positive effects on metabolism and longevity in mice. But of course, this is still only a mouse study.

Always, regarding nutraceuticals—food or elements of food obtained from plant or animal origin with significant medical or health benefits—an AI-powered drug discovery project will be trained on natural ingredients to create novel longevity-focused nutraceuticals after Insilico Meicine and SRW partnered to advance longevity science through the power of AI .

The professor Shinsuke Yuasa from Tokyo has been focusing on AI drug development in Longevity for many years, by utilizing convolutional neural networks (CNN)—deep neural networks commonly applied for visual imagery analysis that expresses how one shape is modified by another. One of it's most recent breakthrough is the development of DeepSeSMo , ?a CNN based scoring system that was trained to quantify the number of senescent cells on biological microscopy slides, since they have distinct morphologies with enlarged and flat cell bodies and distinct aggregation heterochromatin, a tightly-packed form of DNA (5th hallmark).

  • This algorithm was tested on tissue treated with various drugs in an attempt to find senolytic or senotherapeutic drugs and four targets were identified: terreic acid, PD-98059, daidzein and Y-27632·2HCl (via Longevity Technology ).

Moreover, investigators at Stanford University School of Medicine and the Buck Institute for Research on Aging, published their findings in a paper titled?“An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging” claiming that by using AI they can build an inflammatory-aging clock, the iAge, predicting how strong or not our immune system is (immune-senescence), since standard immune metrics used to identify individuals most at risk for developing single or even multiple chronic diseases of aging are lacking.

So, while the immune system is important for fighting diseases, it was only in the past few decades that it has become apparent that inflammatory components of the immune system?are often chronically elevated in aged individuals and associated with an increased incidence of cancer, cardiovascular disease, neurodegenerative disorders, and this have led to the concept that inflammation plays a critical role in regulating physiological aging.

Regarding aging clocks, ExplaiNAble BioLogical Age (ENABL Age) is an AI framework for interpretable biological age . ENABL Age is a computational framework that combines ML models with explainable artificial intelligence (XAI) methods to accurately estimate biological age with individualized explanations. ENABL Age clock was significantly correlated with chronological age.

On August 24, 2020,?Yumanity?Therapeutics?(a clinical-stage biopharmaceutical company that is accelerating the revolution in the treatment of neurodegenerative diseases) and Proteostasis Therapeutics?(a clinical stage biopharmaceutical company developing small molecule therapeutics to treat diseases caused by dysfunctional protein processing) announced that they have entered into a merger agreement, to leverage their common scientific expertise in protein misfolding (Source ) (6th hallmark). Yumanity’s drug discovery platform was designed to enable a rapid screening for potential disease-modifying therapies by overcoming toxicity of misfolded proteins in neurogegenerative diseases.

  • On June 6, 2022 , Yumanity sold its most advanced experimental drug—which is being tested as a treatment for Parkinson's disease, among other conditions—as well as its unpartnered, discovery-stage product candidates to Johnson & Johnson's Janssen division for $26M in cash.

Gero (2015), working in the field of longevity, is a pre-clinical stage company aiming to create therapeutics through the use of its GERO.AI platform, that utilizes whole-exome sequencing data for in-human AI Drug Discovery.

Gero also has a platform called GeroSense , which creates digital biomarkers to measure health changes via smartphone with a precision blood test. GeroSense is a health app on our smartphone that provides digital biomarkers of health and resilience (the recovery rate after stress such as having a cold, exhausting physical activity etc). But instead of simply counting the total number of steps taken each day, GeroSense predicts biological age acceleration in years of life gained or lost, due to healthy or unhealthy lifestyle and nutrition choices. Nutrient sensing—cells ability to?recognise?and respond to fuel substrates such as glucose—is also gradually declining as we age. Current evidence indicates that increased nutrient signaling accelerates aging. While decreased nutrient signaling—achieved with caloric restricted diets—is promoting healthspan and longevity (7th hallmark).

In January 2023, Gero announced that it had entered a research collaboration with Pfizer to discover potential targets for fibrotic diseases, using large-scale human-based data.?

On October 18, 2023, Gero closed $6M in a Series A extension round (for a total of $13.5M). The round was led by Melnichek Investments (a Cyprus-based VC firm that seeks to improve the quality of human lives by funding and supporting promising, potentially high-impact, ML startups) with the participation of VitaDAO and Leonid Lozner.

Twin Health is a revolutionary Precision Health platform combining IoT Sensors, ML and Medical Science to reverse chronic diseases like diabetes and improve human metabolic health. Twin Health announced in 2022 that it has conducted a randomized controlled trial to develop India’s first AI-powered technological therapy , called Whole Body Digital Twin, for the remission of type 2 diabetes.

Traf2- and Nck-interacting kinase (TNIK) has emerged as a key regulator of pathological metabolic signaling in several diseases and is a promising drug target. Originally studied for its role in cell migration and proliferation, TNIK possesses several newly identified functions that drive the pathogenesis of multiple diseases. Specifically, researchers have evaluated TNIK's newfound roles in cancer, metabolic disorders, and neuronal function. TNIK signaling appears to converge on four critical hallmarks of aging : cellular senescence, deregulated nutrient sensing, chronic inflammation, and altered intercellular communication. TNIK's contribution to these processes implicate it as a possible contributor to aging-related pathology, particularly by promoting conditions like cancer and metabolic dysregulation (TNIK as a Potential Target for Age-Slowing Therapeutics ).

Cellino Biotech founded in 2017 by Nabiha Saklayen is using AI and ML to automate stem cell production, for stem cell-derived regenerative medicines (8th hallmark) for Parkinson’s, diabetes, heart disease and many more. Cellino’s platform combines label-free imaging and high-speed laser editing with ML to automate cell reprogramming, expansion and differentiation in a closed cassette format, enabling thousands of patient samples to be processed in parallel in a single facility, combining biology, laser physics, gene editing tools and ML.?

Cellino, a closed loop cell therapy manufacturing company, has raised so far $96M by Leaps by Bayer, 8VC, Humboldt Fund, Felicis Ventures and Khosla Ventures. Khosla Ventures apart Cellino, has invested also in

  • CellFE , that has developed a scalable, high throughput microfluidic technology for the efficient delivery of gene-editing molecules into cells,
  • Bionaut , developing microscale robots to deliver biologics or small molecule therapies locally to targeted disease areas and
  • Liberate Bio , using automation, in vivo high-throughput screening and ML to accelerate discovery of novel extrahepatic delivery vehicles.

For example, Cellino Biotech is using a unique blend of lasers and ML to transform the manufacturing process of stem cells. They are the only company using this approach, and that convergence lets them produce stem cells in a scalable way for the first time. Cellino uses image-guided ML to characterize the highest quality stem cells. They want to live in a world where it’s possible to make therapies derived from our own stem cells and tissues?(because they don’t require immunosuppression), so in order to achieve their goal, they are pursuing collaborations with cell therapy developers to move programs through the clinic very quickly (Source ).

On October 4, 2021, a review on GlyNAC (a combination of Glycine and N-Acetylcysteine) supplementation as a novel nutritional approach to improving declines associated with aging was published, analyzing published research on the effects of GlyNAC supplementation on various components of aging, and concluded that emerging evidence supports that GlyNAC could play a role in the overall health of humans as they age (Source ).

  • In particular, emerging evidence from human studies showed that GlyNAC influences five of the nine hallmarks of aging, including mitochondrial dysfunction, altered intercellular communication, dysregulated nutrient sensing, genomic toxicity and cellular senescence. Altered?intercellular communication is another of the integrative hallmarks of aging (the 9th in particular), but is mainly caused by other hallmarks, particularly cellular senescence and inflammation.

On June 15, 2013, it was announced that algorithms have led to the discovery of three drugs that have the potential to delay the effects of aging (AI and anti-aging research: Unveiling the latest drug discovery ). In particular, a group of researchers from the University of Edinburgh developed an innovative method that employs AI to identify senolytic drugs, by leveraging data from over 2,500 chemical structures extracted from past studies, and training a ML model to recognize the essential characteristics associated with chemicals possessing senolytic activity.

For more:

Albert Einstein, the famous mathematician and scientist, once said:

“There is something essential about the ‘now’ which is outside the realm of science”.

What he probably meant was:

“If the past is t=10 years ago from “now” and the future is t=10 years ahead from “now” in a symmetrical reality, what is then “now” in terms of time? Zero??A state of zero time?”.

Two Sigma Ventures Two Sigma Ventures

Two Sigma Ventures invests in early-stage companies across many industries spanning enterprise SaaS, fintech, techbio, consumer tech, crypto and more. Two Sigma is proud to be an equal opportunity workplace and does not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity/expression, age, status as a protected veteran, status as an individual with a disability, or any other applicable legally protected characteristics.

On September 14, 2022, Two Sigma Announced $400M in New Funds to Fuel Data Science and Software-Driven Innovation in Early and Growth Stage Startups . This bringings their assets under management to over $1.8B, and celebrates their 10th year of backing founders at the leading-edge of data and computing. Regarding TechBio they invest into:

  • ?? Cajal Neuroscience is a drug discovery company built for one purpose: to deliver new medicines that give life back to patients suffering from neurodegenerative disease.
  • ?? Enveda Bioscience is a drug discovery company focused on identifying new therapeutics derived from the natural world, beginning with the plant kingdom. Enveda has built an advanced “search engine” using metabolomics and advanced ML to catalog and map new drugs that can be derived from the plant kingdom.
  • ?? Exai is a next generation AI-powered liquid biopsy company.?Exai Bio’s next-generation RNA-based platform delivers actionable insight into cancer biology from a simple blood draw.
  • ?? Hexagon Bio is a data-driven biotech developing targeted small molecule therapeutics. Their proprietary platform combines data science and synthetic biology to discover and engineer drugs from DNA sequences. They are mining fungal genomes for inspiration for the next generation of targeted therapies for diseases with unmet needs. Since 99% of microbial genomes have yet to be sequenced vast troves of new medicines are waiting to be surfaced using DNA sequencing, ML and synthetic biology. Their TICker algorithm computationally predicts microbial secondary metabolites that inhibit human disease proteins and prioritizes them among thousands of candidates. While their HEx platform produces novel compounds using heterologous expression, an approach that allows forced expression of the secondary metabolites of interest. The result is new chemical entities based on novel chemical scaffolds, potential medicines that may offer entirely new ways to treat disease.
  • ?? Insitro (2018, South San Francisco, California) is a drug discovery company that operates an automated lab equipment running on algorithms that use its own in vitro disease models. In particular, Insitro’s predictive models are grounded in human data (genetic, phenotypic and clinical data) using ML. Moreover, they combine patient-derived induced pluripotent stem cells (iPSCs), genome editing, high content cellular phenotyping and ML to build in vitro models of disease. The outcome is an integrated model of disease spanning in vitro cellular systems and in silico ML models—namely an insitro model that allows them to differentiate between cell states at much finer granularity and predict disease-relevant clinical traits.
  • ?? The New York-based Kallyope , that has taken the impossible task of mapping out the bidirectional communication between the central and the enteric nervous system and the microbiota influencing these interactions (the gut-brain axis) linked to metabolic and gastrointestinal diseases as well as central nervous systems disorders (autism and Parkinson’s disease). In 2922,?has closed a Series D financing worth $236M . The company right now has three compounds into phase 1 clinical trials (for type 2 diabetes, obesity and diseases of the gastrointestinal barrier) and many more in preclinical phase.
  • ?? Osmo , founded in 2023 in Cambridge, Massachusetts as a spinout from Google Research by Alex Wiltschko , uses ML and has created a map of odor giving computers a sense of smell to improve the health and wellbeing of human life. They are now embarking on end-to-end reproduction of a captured scent and they call this an Osmograph, and believe that like a photo or a song an Osmograph has the power to activate treasured memories and evoke profound emotions.
  • ?? Xilis , is a pioneering biotechnology company developing its MicroOrganoSphere (MOS) technology—a new standard in patient-derived micro-tumor production—to guide precision therapy for cancer patients. For that reason, Xilis is using MOS and AI-driven algorithms, to develop a Xilis Response Score? for the clinic, and in 2023 closed an extension of over $19M to its Series A financing round, bringing the total amount raised to over $89M.
  • ?? And the well known Recursion Pharmaceuticals , Terray Therapeutics and Verge Genomics .


?? MOLLEO ?? Efficient Evolutionary Search Over Chemical Space with Large Language Models

  • Molecular discovery, when formulated as an optimization problem, presents significant computational challenges because optimization objectives can be non-differentiable.
  • Evolutionary Algorithms (EAs), often used to optimize black-box objectives in molecular discovery, traverse chemical space by performing random mutations and crossovers, leading to a large number of expensive objective evaluations.
  • In this work, a group of researchers ameliorated this shortcoming by incorporating chemistry-aware Large Language Models (LLMs) into EAs. Namely, they redesigned crossover and mutation operations in EAs using LLMs trained on large corpora of chemical information.
  • They performed extensive empirical studies on both commercial and open-source models on multiple tasks involving property optimization, molecular rediscovery, and structure-based drug design, demonstrating that the joint usage of LLMs with EAs yields superior performance over all baseline models across single- and multi-objective settings. Finally, they demonstrated that their algorithm improves both the quality of the final solution and convergence speed, thereby reducing the number of required objective evaluations.



Until next time ????


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