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SOFTWARE (NON-INTERNET/MOBILE) | Healthcare Software
atomwise.com

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Founded Year

2012

Stage

Grant | Alive

Total Raised

$176.42M

Last Raised

$2.3M | 1 yr ago

About Atomwise

Atomwise uses deep learning neural networks to help discover new medicines. Atomwise achieves results for new drug hit discovery, binding affinity prediction, and toxicity detection. Atomwise predicts drug candidates for pharmaceutical companies, start-ups, and research institutions. It is currently using computational drug design to design drugs against COVID.

Atomwise Headquarter Location

717 Market Street Suite 800

San Francisco, California, 94103,

United States

650-720-8923

Latest Atomwise News

BioSymetrics Expands Leadership Team To Support Rapid Growth

Sep 28, 2021

BioSymetrics Expands Leadership Team To Support Rapid Growth Key Appointments Bring Highly Relevant Experience in Artificial Intelligence and Machine Learning for Drug Discovery Author: Sep 28, 2021 9:30 AM EDT BOSTON and TORONTO, Sept. 28, 2021 /PRNewswire/ --  BioSymetrics , an AI-powered drug discovery company, today announced the appointments of Stacie Calad-Thomson as Chief Strategy Officer and Head of Drug Discovery, Matt Fusco as Chief Operating Officer, and Amanda Guisbond as Vice President of Marketing and Communications. BioSymetrics integrates clinical and experimental data using machine learning to navigate human disease biology and advance precision medicines. Unlike other AI-powered drug discovery startups, BioSymetrics utilizes electronic health record data and human-relevant disease models to bring clinical insights, validated in vivo, into the scientific discovery process. BioSymetrics then applies its patent pending Contingent AI ™ to denoise, debias and integrate this clinical data for use across a phenotype-driven, therapeutic discovery process. BioSymetrics currently works with life science and health system partners - including Sema4, Northwell Health and Janssen, The Pharmaceutical Companies of Johnson & Johnson - to leverage diverse datasets, apply its framework to advance our understanding of disease, and progress therapeutic discovery. BioSymetrics is currently exploring, with and without partners, preclinical development of assets in neurogenerative, cardiovascular and rare disorders. These three leadership appointments support BioSymetrics' plans to operationalize its proprietary Elion ™ platform and accelerate partner and pipeline development: Stacie Calad-Thomson, Chief Strategy Officer and Head of Drug Discovery Stacie will guide the company on its drug discovery strategy, with a focus on human-relevant disease biology, and progressing beyond protein targets. Stacie is a rising star in the industry, having already held positions of increasing responsibility at GSK, Atomwise and the ATOM Consortium, in addition to her work consulting with many of the startups currently using machine learning or genomics data to spearhead drug discovery programs. "The current pharma model is plagued by high failure rates and attrition. Nearly 90 percent of drug discovery programs that enter clinical trials fail, and most are due to lack of efficacy," said Stacie. "Having worked in the industry for 15 years, I've seen how clinical data are siloed from discovery data, and that lessons learned go un-shared between, or even within, these organizations. What excites me about BioSymetrics - and why I've decided to join full time after consulting with both BioSymetrics and its competitors in the space - is its application of real-world patient data and human-relevant disease models to drug discovery. This is a compelling, modern approach that I'm eager to help bring to more partners as we build, together, a pipeline of human disease-ready, AI-derived medicines. "  Matt Fusco, Chief Operating Officer Matt is an entrepreneur and executive leader with repeat experience helping early-stage companies bring new and innovative solutions to market. With a strong operational and business development background, Matt has helped numerous companies navigate complex and emerging markets to provide actionable direction that drives client adoption and improves internal processes and execution. Before BioSymetrics, Matt was co-founder of Barometric, a data company providing measurement and identity services to advertisers that was sold successfully to Claritas in 2018. Amanda Guisbond, Vice President of Marketing and Communications Amanda is a career marketer and corporate communicator with a focus on emerging companies in the digital health and life sciences sectors. Amanda brings highly relevant experience to BioSymetrics from Recursion, where she led marketing and communications before the digital biology company's successful IPO earlier this year. Previously, Amanda also led communications for Amwell, a national telehealth company at the front lines of the COVID-19 pandemic and was part of the team that developed the initial communications and marketing strategy for Moderna. Said Anthony Iacovone, Co-Founder and Chief Executive Officer of BioSymetrics: "We are humbled and excited to bring on these three seasoned leaders, all incredibly skilled at what they do, to the growing leadership team at BioSymetrics. Stacie's experience in AI and drug discovery has already helped to refine our strategy around partnering, platform development and pipeline prioritization. I've had the pleasure of working with Matt before, an executive who is laser focused on execution while building team morale and know he will help us deliver on our vision. Like Stacie, Amanda has already impressed me with her knowledge about the industry and approach to messaging and communication strategy. This is the team that will accelerate our growth and help elevate BioSymetrics as a leader in our industry." For more information on BioSymetrics, please visit www.biosymetrics.com . About BioSymetrics BioSymetrics is an AI-powered drug discovery company with a mission to bring the clinic to the bench and back. BioSymetrics integrates clinical and experimental data, using its patent pending Contingent AI TM, to effectively navigate human disease biology and advance precision medicine. The company partners with a diverse network of life science and health system partners on end-to-end drug discovery, from gene disease prioritization to mechanism of action to clinical trial and small molecule design. BioSymetrics is a remote-first company with people clusters in Boston and Toronto. For more information, please visit www.biosymetrics.com . View original content: https://www.prnewswire.com/news-releases/biosymetrics-expands-leadership-team-to-support-rapid-growth-301386316.html

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Expert Collections containing Atomwise

Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.

Atomwise is included in 5 Expert Collections, including AI 100 2018.

A

AI 100 2018

200 items

A

Artificial Intelligence

7,904 items

This collection includes startups selling AI SaaS, using AI algorithms to develop their core products, and those developing hardware to support AI workloads.

D

Digital Health 150

300 items

2019's cohort of the most promising digital health startups transforming the healthcare industry

B

Biopharmaceuticals

5,882 items

Companies involved in the research, development, and commercialization of chemically- or biologically-derived therapeutic & theranostic drugs. Excludes vitamins/supplements, CROs/clinical trial services.

D

Digital Health

11,292 items

Technologies, platforms, and systems that engage consumers for lifestyle, wellness, or health-related purposes; capture, store, or transmit health data; and/or support life science and clinical operations. (DiME, DTA, HealthXL, & NODE.Health)

Atomwise Patents

Atomwise has filed 6 patents.

The 3 most popular patent topics include:

  • Classification algorithms
  • Machine learning
  • Statistical classification
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11/6/2019

8/3/2021

Artificial neural networks, Machine learning, Classification algorithms, Spatial data analysis, Statistical classification

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Artificial neural networks, Machine learning, Classification algorithms, Spatial data analysis, Statistical classification

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Grant

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