Latest News 🆕 on TechBio
“Our world is built on biology and once we begin to understand it, it then becomes technology." Ryan Bethencourt cofounder & CEO at Wild Earth, Partner at Babel Ventures and cofounder at IndieBio
News 🆕 and Trends
➡️ On October, 11, 2023, Antiverse and GlobalBio, Inc. have extend their collaboration to advance antibody cancer therapeutics.
, a biotechnology company developing a computational antibody drug discovery platform, and GlobalBio, an antibody engineering company developing methods to engineer improved and more developable therapeutic antibodies, just announced that they will be extending their collaboration to advance immune checkpoint inhibitors in cancer therapy. The initial collaboration successfully resulted in the generation of a panel of anti-PD-1 antibodies (programmed death-ligand 1 or PD-L1 also known as cluster of differentiation 274, CD274, has been speculated to play a major role in suppressing the adaptive arm of immune systems) with diverse binding and functional profiles, with two candidates from this panel now entering preclinical development.Antiverse’s proprietary AI-driven Antibody Discovery platform, uses state-of-the-art ML techniques and advanced cell line engineering to develop antibodies for challenging drug targets, alongside GlobalBio’s ALTHEA semisynthetic libraries for the discovery and optimisation of antibody-based therapeutics.
Since its is difficult to discover antibodies against GPCRs receptors because of cells with low receptor count and because of antibody libraries with poor specificity, at Antiverse they have built a discovery platform that develops cells with high receptor counts (1M per cell) and antibody libraries (de-novo target-specific libraries focused on functional epitopes) with high specificity against each target. Subsequently, in their lab they screen the target-specific libraries against cells with high receptor counts to reach a high number of binders and the outputs are then sent for deep sequencing and AI-based clustering.
➡️ Vevo Therapeutics, a biotechnology company using its Mosaic in vivo drug discovery platform and AI models to uncover better drugs, was launched last year with an oversubscribed and upsized $12M seed financing round. The Mosaic platform is the first platform to make in vivo data generation scalable, with single-cell precision, while capturing patient diversity in drug response. In a single in vivo experiment, Mosaic can measure how a drug impacts cells from tens to hundreds of patients, generating millions of datapoints on drug-induced changes in gene expression.
➡️ Another AI drug discovery company utilising data at single-cell resolution to identify cell-state transitions that drive disease is Cellarity, a life sciences company founded by Flagship Pioneering. Until now, the dominant approach in drug discovery has been to reduce disease biology into a single molecular target and then leverage high-throughput screening to identify molecules that bind to these targets. But at Cellarity, they focus on the whole cell because, most often, a disease isn’t driven by one mechanism or protein, accordingly they use single-cell technologies to identify the cellular drivers of the transition from health to disease and then apply DL models to create drugs that reverse disease at the cellular level.
On July 27, 2023, Cellarity announced that The Galien Foundation, the premier global institution dedicated to honouring innovators in life sciences, named Cellarity a 2023 Prix Galien USA Award nominee for "Best Startup. And in October, 2023, Cellarity announced a partnership with the Chan Zuckerberg Initiative to drive innovation in ML algorithms for single-cell analysis via support of the Open Problems in Single-Cell Analysis initiative.
“There are more than 1,500 algorithms developed for single-cell data, and understanding the deep complexity of cells captured by single-cell technologies requires robustly evaluating the performance of these methods.”
Diogo Camacho, Ph.D., Vice President of Computational Biology at Cellarity
➡️ Quris, has an AI Chip-on-Chip platform that allows automated testing of thousands of drugs on miniaturised Patients-on-a-Chip, while next-generation nano-sensors allow for continuous monitoring of the responses from each miniaturised organ to these drugs. Then, their ML classification algorithm is trained with the data continuously generated in this high-throughput system. On September 28, 2023, Quris announced the extension of its collaboration with Merck to leverage Quris-AI platform’s ability to effectively identify liver toxicity risks in a selection of drug candidates.
“Based on the results of our initial collaboration, we are looking forward to exploring how its BioAI platform can advance our drug development and testing programs, and working towards an AI-enabled IND process that reduces the reliance on animal testing.” Said Danny Bar-Zohar, Global Head of Research & Development at Merck
The Quris BioAI platform (29 granted and pending patents) delivers
best-in-class drug safety, through its advanced ML and generative AI models, which are trained on Quris-AI’ highly predictive, proprietary data, that are generated from its AI-based patient-on-chip platform. This dramatically accelerates and cuts costs of drug development, and avoids the potentially disastrous pitfalls of traditional animal testing.
➡️ Molecular Devices, one of the leading providers of high-performance bioanalytical measurement solutions for life science research, pharmaceutical and biotherapeutic development, has just introduced the CellXpress.ai™ an automated cell culture system for screening, a revolutionary ML-assisted solution that standardises the entire cell culture journey to deliver consistent, unbiased, and biologically relevant results at scale. The CellXpress.ai™ is an AI-driven cell culture innovation hub that gives your team total control over demanding cell culture feeding and passaging schedules (eliminating time in the lab), while maintaining a 24/7 schedule for growing and scaling multiple stem cell lines, spheroids or organoids. All of it backed with the assurance of a full event log to confirm on-time feedings and critical task execution with complete digital microscopy records.
Moreover, Molecular Devices is offering
an AI-based software that provides Photoshop-like tools for image annotation, and
the ImageXpress® Confocal HT.ai High-Content Imaging System, designed to help researchers advance phenotypic screening of 3D organoid models. The ImageXpress® utilises a seven-channel laser light source with eight imaging channels to enable highly multiplexed assays while maintaining high throughput by using shortened exposure times. Water immersion objectives improve image resolution and minimise aberrations so scientists can see deeper into thick samples. Moreover, the combination of MetaXpress® software and IN Carta® software simplifies workflows for advanced phenotypic classification and 3D image analysis with ML capabilities and an intuitive user interface.
➡️ Diadem is a EU project developing a platform for organic electronics providing a one-stop-shop solution from digital discovery to experimental verification by linking the virtual screening of small molecule candidates with the chemical supply chain. They offer an one-stop solution for searching, refining and supplying chemicals, with the power of cheminformatics and molecular modelling, without users having to worry about physical computing infrastructure while offering the following benefits:
Completely novel chemical solutions,
Robust property prediction,
Candidate available from chemical supply chain, and
One-stop integrated platform for fast service from discovery to lab.
Diadem has three participants:
The Materials Innovation Factory, located at the University of Liverpool, aiming to accelerate product development and gain competitive advantage through smarter, faster and more precise ways of working, using world class automated lab equipment.
Nanomatch, an SME based in Germany, developing predictive, adjustable virtual design tools for organic electronic applications. Using a multiscale simulation approach, they translate molecular properties to the device scale, and thereby bridge the gap between fundamental chemistry and device design.
Mcule that is creating the best online drug discovery platform, and provides the highest quality database integrated with molecular modelling searching tools and cloud services to help biotech and pharma companies find new drug candidates quickly and efficiently. Mcule’s services include
Compound sourcing, based on a high-quality compound database, advanced compound selection, automated price optimisation and professional delivery service,
Hit identification tools, their Workflow Builder is a cost-effective, cloud-based solution for identifying new chemical starting points by structure- and ligand-based virtual screening and screening library design, and
Lead optimisation tools, intuitive, easy-to-use modelling applications specifically designed for bench scientists to evaluate and generate ideas in the lead optimisation process.
The consortium members just held their 4th progress meeting in Heidelberg, Germany between the 12th and 13th of October, 2023. The meeting mainly focused on the development of the alpha platform version and the refined and extended DiaDEM chemical database.
➡️ A team of Chinese scientists, from the Shanghai Institute of Materia Medica under the Chinese Academy of Sciences, just proposed a new AI tool that may help significantly speed up the process of discovering drugs. The PBCNet, or pairwise binding comparison network, is designed for comparing the relative binding affinity among similar ligands - molecules or ions that bind to larger molecules. A simulation-based experiment showed that active learning-optimised PBCNet may accelerate structure optimisation by 473% and save computing resources by an average of 30%. The team also established an open-source web service with an easy-to-operate graphical interface for the convenience of users: Link.
“If only the human body could handle trauma as well as biotechnology stocks do”-Alex Berenson
➡️ DevsHealth is a DeepTech company using AI, Real-World Data (RWD) and molecular modelling to improve new anti-infectious treatments development. Their AI-based technology helps to optimise a rational design of new drugs, anticipate potential side effects and its behaviour in our body (predict ADME properties). By integrating, standardising and curating several public-source databases at DevsHealth they are able to manage around 2.5M gene expression experiments, almost a million bioactive compounds and their biological activities and thousands of proteins and structures.
In 2023, the Bengaluru-based Foundation for Neglected Disease Research (FNDR) and the Spanish DevsHealth announced a collaboration to develop broad-spectrum antiviral agents for infections caused by flaviviruses such as dengue, Zika, West Nile virus, and Japanese encephalitis, among others. DevsHealth will be in charge of in silico studies and chemistry efforts and the FNDR will manage all in vitro and in vivo experiments.
➡️ Cortex Discovery has a modern ML approach to rapidly and confidently screen a vast number of compounds and to identify high quality compounds with higher chances of success in progressing through preclinical drug discovery. Their system directly models the chemical processes of the interactions between targets and arbitrary drug-like molecules, enabling then to generalise their findings to a wider range of compound classes and new targets that may not have existing experimental data. So far, cortex discovery has already achieved several significant technical milestones in their first large-scale molecular docking prototype. They offer the following services:
Screen large libraries or virtually generate de novo compounds,
Predict on-target interactions (hit discovery),
Predict off-target interactions (polypharmacology), and
Drug metabolism and toxicity, ADMET, profiling.
➡️ CardiaTec Biosciences, spun-out of the University of Cambridge in September 2021, is applying AI on large-scale multi-omic data to develop the next generation of cardiovascular disease drug targets. CardiaTec’s AI driven multi-omics analysis platform can unravel relationships from gene variation, methylation and expression, to their connection to proteomic and metabolomic functions, in order to uncover next generation cardiovascular disease drug targets, by exploring computationally enabled target-drug interactions to support the development of novel drugs into the clinic. In 2022, CardiaTec completed a £1.4M pre-seed fundraise led by Apex Ventures and Laidlaw Ventures.
➡️ Nanoform works to improve the lives of patients globally by overcoming drug development and delivery challenges through game-changing technologies and novel formulation capabilities such as:
A multi-patented Controlled Expansion of Supercritical Solutions (CESS®) technology that enables the creation of API (Active Pharmaceutical Ingredients) nanoparticles directly from solution. The process can be applied to most small molecules, with a high success rate.
A biological nanoforming technology that can deliver large-molecule drug particles as small as 50 nm while retaining biological activity. It’s effectiveness has been demonstrated on proteins in the 1-150 kDa range, and it is capable of engineering particle sizes to specific requirements.
An experienced formulation development team that designs and develops flexible dosage forms of nanoformed drug substances to meet preclinical and clinical development as well as life-cycle needs. And
GMP manufacturing capabilities for the manufacture of nanoformed clinical-grade API’s for their customers and partners.
On October 23, 2023, Nanoform announced that it has granted AstraZeneca a global online STARMAP® license. STARMAP® is a digital AI version of the CESS® technology that enables in-silico experiments to determine which molecules should be nanoformed. STARMAP® Online creates the opportunity for clients to perform large numbers of in-silico CESS® experiments from their desktop. The license will enable AstraZeneca to screen molecules from drug discovery through to lifecycle management. As part of this licensing agreement, Nanoform will receive access to compound libraries and large data sets to undertake STARMAP® screening and propose innovative product development concepts and strategies in collaboration with AstraZeneca.
➡️ Boltzmann Labs is a new drug discovery company in India with three oncology and two auto-immune candidates in its pipeline, offering
BoltChem: an AI Chemistry Studio for drug design for discovering novel small molecules. Exploration of chemical space and property prediction of small molecules automated with BoltChem.
Rebolt: a next generation AI synthesis tool for chemists to plan and design reaction pathways within a few minutes by just a few clicks. Synthesis made Effortless, Economical and Expeditious.
BoltBio: offering pathway analysis, network biology, potential target identification, Interaction predictions and more.
BoltPro: a studio to engineer proteins, peptide drugs and antibodies.
It helps understand the effects of mutations on molecular properties, multi-objective antibody design, peptide design, protein folding, and optimisation of latency.
At Boltzmann they contribute to open-source communities Bayes Labs (a community that coordinates from remote locations to produce quality work in the fields of AI and Drug Discovery research) and ChemBioAI.
➡️ The British techbio innovator Etcembly, established in 2020, is coming out of stealth mode kickstarting the next generation of immunotherapies with a pipeline of best-in-class T cell receptor (TCR) therapeutics designed using generative AI.
TCRs constitute one of the most promising classes of emerging therapeutics, although TCRs are amongst the most complex facets of immune biology.
For this reason, Etcembly is building the world’s largest ML database and unmatched immunology expertise to deliver the safest and most powerful TCR immunotherapies through rapid computer-assisted engineering. Their platform EMLy™ uses generative large language models (LLMs) to rapidly predict, design and validate TCR candidates (deep sequencing). EMLy™ scans hundreds of millions of TCR sequences then engineers them to achieve low pM affinity and eliminate cross-reactivity.
The company’s lead therapeutic programme, ETC-101, is an AI-designed bispecific T cell engager that targets PRAME, an antigen present in many cancers but absent from healthy tissue. Etcembly has advanced ETC-101 to this stage (lead optimisation) in 11 months, compared with 2+ years for conventional TCR discovery and engineering pipelines.
➡️ On October 17, 2023, Servier, a global independent pharmaceutical group, and Owkin, a French American AI drug discovery company, announced a partnership to use AI to advance and accelerate better-targeted therapies across multiple disease areas, including oncology. Owkin will apply ML to Servier’s extensive clinical data in order to deliver novel insights into the underlying biology of disease, identifying the patient populations most likely to benefit from Servier’s new therapies.
Owkin is a full-stack AI biotech offering:
Multimodal patient data:
Abstra will host a metadata catalog to enable researchers and data scientists to discover collaborators and datasets, enhancing and expediting AI biomedical research.
Substra is a ready-to-use, open source federated learning (FL) software developed by Owkin, now hosted by the Linux Foundation for AI and Data, that enables the training and validation of ML models on distributed datasets.
MOSAIC is a landmark research project to create a multimodal dataset with spatial transcriptomes from 7,000 patients in 7 cancer types. This is the largest spatial omics atlas to date.
Subgroup discovery: They apply AI to multimodal, KOL-curated data to subtype patients and identify novel biomarkers to inform drug discovery, de-risk clinical trials and develop and deploy diagnostics in clinical practice.
AI drug discovery: They deliver novel drug targets and optimise drug positioning.
AI drug development: They combine ML methodologies, patient data and innovative modalities to increase the probability of success of clinical trials.
AI diagnostics: They pre-screen for biomarkers, and predict outcomes — giving healthcare providers a fuller picture of a patient’s disease. This means more patients can benefit from targeted therapies.
MSIntuit™ CRC is a CE-marked AI diagnostic that provides a prescreen approach with digital pathology. MSIntuit is used for Microsatellite instability (MSI), genomic biomarker that plays an important role in the treatment of colorectal tumours (CRC) patients, from H&E WSI, and performed the first successful blind validation confirming its robustness for clinical applications.
RlapsRisk™ BC is an AI diagnostic to help pathologists and oncologists determine the right treatment pathway for early breast cancer patients. RlapsRisk BC assesses the risk of distant relapse at 5 years of ER+/HER2- early invasive (ei) Breast Cancer patients, post surgery, from HES (hematoxylin-eosin-safran)-stained whole slide images (WSI) and clinical data.
Owkin is founder-led by Thomas Clozel, MD, Oncologist, and Gilles Wainrib, PhD, Professor of Machine Learning, trusted by 8 biopharmas with strategic deals with Sanofi and BMS, first in class in AI diagnostics and well-funded with million dollars (a total of $304.1M) raised from leading biopharma companies (Sanofi & BMS) and venture funds (Fidelity, Google Ventures & BPI, among others).
➡️ On October, 25, 2023, Algorae Pharmaceuticals has 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 will be 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.
Until next time,
PS
In this GEN webinar (Register here), Dr. Shelby Wyatt VP of Global Pharma Strategy at Flywheel.io (a cloud-based company with a medical imaging AI platform) will discuss how AI-based medical imaging helps imaging/data scientists accelerate drug development initiatives and how Flywheel builds reliable, scalable medical imaging solutions that seamlessly integrate advanced AI technology from NVIDIA and other technology partners to enable robust imaging data management and analysis. During drug screening Flywheel can offer the following solutions to the imaging research labs:
Metadata management with search
Automated pre-processing & pipelines
Machine learning workflow
Customisation via APIs, Python, & Matlab
Provenance
BIDS support, and
Secure collaboration.
On June 27, 2023, Flywheel announced it has raised $54M in Series D funding co-led by Novalis LifeSciences LLC and NVentures, NVIDIA’s venture capital arm. Microsoft also participated in the round, along with insiders Invenshure, 8VC, Beringea, Hewlett Packard Enterprise, Intuitive Ventures, iSelect, Gundersen Health System, Seraph, and Great North Ventures. Faegre Drinker Biddle & Reath LLP served as counsel to Flywheel in connection with the financing.
What are decent external sources you follow to keep up with major trends in drug development?