Ordaōs Announces a Joint Development Agreement to Create Novel Therapeutics for AML12/19/2022
NEW YORK, NY, December 19,2022 /PRNewswire/ -- Ordaōs, a biotechnology company designing novel mini-proteins to help drug hunters deliver life-saving treatments, today announced a joint development agreement to create new therapeutics for two novel targets in Acute Myeloid Leukemia (AML) with Yatiri Bio, a biotechnology company that has developed a proprietary platform that links patient proteomic and clinical data to context-specific ex-vivo model systems to drive efficient drug development and advance personalized medicines.
Yatiri Bio will utilize its rich knowledge base of global proteomics from AML patient samples and matched model systems to identify two cell surface therapeutic targets for high-risk AML. Ordaōs, using their proprietary Ordaōs Design Engine, will create a panel of in silico de novo protein candidates and will be responsible for in vitro validation of those leads. Recent advances in machine learning, mass spectrometry, bioinformatics, and ex-vivo model systems have the potential to drive a new era of precision oncology for AML patients and the development of therapeutics specifically for relevant patient subsets.
"We are very excited by this partnership and the potential of providing effective treatment options for AML, an aggressive blood cancer," said Ziwei Liang, CSO of Ordaōs. "With Yatiri Bio's ability to identify drug targets combined with Ordaōs capability in designing and creating mini-proteins, we see great promise in helping to discover therapeutic targets for diseases with unmet needs, like AML."
According to the Leukemia & Lymphoma Society, AML is one of the most lethal blood cancers that takes more than 10,000 lives in the U.S. each year. While there are approved treatments for this disease, there remains an urgent need for new therapeutics. Among adults over the age of 60, only about one in four AML patients survive five years after diagnosis.
Once developed, target leads will be tested in Yatiri Bio's portfolio of matched and patient-derived cellular models, ProteoModelsTM, informed with clinical proteome data and extensive ex-vivo testing of Standard of Care (SoC) therapies. Once the targets are validated, Ordaōs and Yatiri Bio will jointly develop these candidates further for an IND submission.
"By working together with Ordaōs, we have the potential to accelerate the development of a novel therapeutic for patients with AML whose current treatment options are very poor," said Pilgrim Jackson, CEO of Yatiri Bio. "Our philosophy is that a global, unbiased evaluation of patient-level data using proteomics and the integration of highly curated metadata results in a far more direct path to producing treatments and identification of the groups for whom these treatments will be most effective. We are thrilled to partner with Ordaōs on this program."
About Ordaōs Ordaōs is a human-enabled, machine-driven drug design company that helps birth novel therapies to reduce patient suffering, improve health, and extend life. Our flagship solution, miniPRO™ mini-proteins, enable drug hunters to deliver safer and more effective treatments in a fraction of the time of traditional discovery methods. To learn more, visit the Ordaōs website, or email email@example.com.
CONTACT: David Longo, CEO of Ordaōs Dave@ordaos.bio
About Yatiri Bio Yatiri Bio has developed a proprietary platform to integrate diverse data streams with proteome-level data to create an efficient path for drug development. Using leading-edge proteomics technology on patient samples, and tailored ex-vivo models, Yatiri Bio delivers insights to its pharma partners regarding drug performance, mechanisms of action, and, most importantly, approach to patient selection. Yatiri Bio uses a pharma partnership model with payments based on the discovery, development, regulatory and commercial milestones. To learn more about Yatiri Bio, please visit www.yatiribio.com or email firstname.lastname@example.org.
CONTACT: Pilgrim Jackson, CEO of Yatiri Bio email@example.com
More About The Ordaōs Design Engine: Ordaōs uses The Ordaōs Design Engine, to deliver true protein property design - leveraging continuous learning loops and proprietary data sets to translate human-targeted product criteria into machine-designed mini-proteins. Starting with amino acids, the Design Engine generates, appraises, and ranks billions of protein sequences and hundreds of thousands of protein structures and properties to create customized miniPRO™ proteins. These proteins are then rapidly evaluated in vitro to provide intelligent feedback on multiple design objectives including protein structure, binding specificity and affinity, solubility, stability, immunogenicity, and developability. This iterative process delivers optimized mini-proteins to meet the client's specific molecular target product profile (mTPP). They are also less likely to cause adverse side effects and are easier and less expensive to test, develop, and manufacture than traditional proteins. Using this approach, the Ordaōs Design Engine creates more ideal, unseen protein leads than others and can accelerate drug candidate development, increasing the probability of more therapeutically effective candidates. All of this provides clients with a high level of confidence in their investigational new drug (IND) applications.
More About Yatiri Bio's Platform: Yatiri Bio has developed an easy-to-use platform (ProteoBrowserTM) that integrates proteome data, metadata, genomics data, computational biology, ex-vivo model sensitivity, and machine learning to revolutionize drug discovery. To date, we have analyzed and curated well over 200 AML proteomics patient samples. Additionally, we have developed a portfolio of cellular models (organoids, cell lines) that have been backed by clinical proteome data that are tailored to match molecularly defined cancer subtypes. These ProteoModelsTM can be used for optimizing patient selection, rational exploration of combination therapies, drug repurposing, identifying resistance mechanisms, and drug discovery with robust and translatable biomarkers from the outset. The incorporation of accurate efficacy models will streamline the entire drug discovery process, guide early research choices, and make it easier and far less costly to match the right therapeutic with the right patients. All of these will drive a new era of precision oncology for patients and the development of therapeutics specifically for relevant patient subsets.