Amplifying High Impact Research for COVID-19

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  • Stanford Medicine

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    Amir Bahmani, PhD

    Algorithms for Infections Disease Detection

    The Snyder Lab at Stanford University is a world leader in analyzing genomes, transcriptomes and other omes. In addition to studying the fundamental principles of regulatory networks and analyzing human variation, Dr. Snyder's lab performs deep omics profiling/big data collection on individuals over time to understand what keeps them healthy and what happens when they become ill or undergo other sorts of changes (e.g. diet, etc). This analysis is applied to solving challenging and mystery diseases, along with disease prognosis.



    The Snyder Lab has developed open source algorithms for early infectious disease detection. The present objective is to apply these algorithms to COVID-19 and deploy it widely.


    "We are trying to find out if information from wearable devices, like FitBit and Apple Watch, can be used to track infectious diseases like COVID-19.


    We hope to be able to predict the onset even before any symptoms start.​ A study is underway and will be enrolling soon. Healthcare workers and high-risk individuals are especially encouraged to enroll in this data tracking research study."

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  • DeepChem

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    Bharath Ramsundar, PhD

    COVID-19 Drug Discovery with DeepChem

    The DeepChem project works to democratize deep learning for science. More specifically, DeepChem aims to provide a high quality open-source toolchain that democratizes the use of deep-learning in drug discovery, materials science, quantum chemistry, and biology. DeepChem is managed by a team of open source contributors. Anyone is free to join and contribute!


    Dr. Ramsundar will provide an overview of current therapeutic development efforts towards COVID-19. He'll review some of the known biological and chemical factors about COVID-19, such as the recently solved structures of the spike-protein on the coronavirus capsid, the structure of the main protease, and some early clinical trial results. He'll then give a brief introduction to the DeepChem library and discuss how deep learning efforts can help with the design of COVID-19 therapeutics.

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  • VeriSIM Life


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    Jyotika Varshney, DVM, PhD

    Simulating Effectiveness of Potential Anti CORONAVIRUS Therapies

    VeriSIM has developed a platform that integrates machine learning with robust models of in vivo pharmacokinetics and pharmacodynamics, enabling faster model development, more accurate prediction, and higher scalability. We leverage existing datasets of physiological outputs from different species to train a model that is physiologically-relevant and translatable across different experimental conditions.


    Dr. Jo Varshney has invited our community to submit new molecules to VeriSIM Life for biosimulation and efficacy screening. She will lead a session introducing the compound screening system VeriSIM Life has developed and how we can collaborate during COVID-19. 

    VSL's approach is to 1) develop mechanistic models relevant to vivo mAb physical/biochemical phenomena, 2) develop in vitro-in vivo scaling models for translating outputs to whole-system contexts, and 3) investigate computational chemistry methodologies for tying compound physicochemical properties to model parameters.


    Dr. Varshney is seeking academic and pharma partnerships for VSL.

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  • infinome

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    Clinton (Cosmo) Mielke, PhD

    Quarantine@Home, Donate Processing Power For Coronavirus Drug Discovery

    Quarantine@Home is a project that lets you donate your spare computer power to finding drugs to target the coronavirus! We leverage the power of the Autodock suite of tools to perform small molecule screening against viral proteins. Possible drugs are sourced from the Zinc Database hosted at the University of California San Francisco

    Developers can access the source code here.


    To accelerate drug discovery efforts for COVID-19, Dr. Mielke has released Quarantine@Home, a collaborative computational drug screening platform.


    Cosmo will introduce how this system works and how we can be involved.

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  • Stanford Medicine

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    Fereshteh Jahaniani PharmD-PhD

    Interventions Discussion w/ Fereshteh Jahanbani, PharmD, PhD in Pharmacology

    Fereshteh hypothesized that a prophylactic COVID-19 treatment including Azitromycin + low dose Losartan+ corticosteroids/NSAID+ VitC might improve patients’ symptoms, especially those with pneumonia. This regimen might decrease hospitalization time and prevent the development of severe illness in high risk population.


    She is also interested in collecting data for current COVID-19 treatments and use statistical tool to find out their efficacy. Finding effective treatment is as important as developing fast and sensitive diagnostic kits to screen everyone. She would like to invite those who would like to take the challenge to this collaborative effort and great cause.


    Studies support that SARS-CoV-2 interaction with human ACE2 is needed for host cell entry and subsequent viral replication. So the question is that if Angiotensin II receptor blockers such as Losartan help till we find a better treatment. Immune-mediated fibrosis and also secondary infection are part of CoV19 pathogenesis. Prophylactic Azithromycin, low dose Losartan, corticosteroids/NSAID and high dose vitC might help to treat the high risk patients.

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  • Building a Robust and Accurate Primer Design Platform for COVID-19

    Tomer detected a set of technical problems with the CDC's COVID-19 primer-probe sets, key components of the diagnostic kits used for testing patients. Issues included hairpin loops and low-complexity regions in the oligonucleotides. Here, he will describe a bioinformatic pipeline to design better candidate primers that pass stringent design criteria.


    Using this pipeline Tomer generated a new set of primers and probes without the aforementioned technical issues of the CDC COVID-19 primer probe sets, and tested their /in silico/ precision and recall using the most recent set of COVID-19 complete genomes from NCBI.

    The ten best primer-probe pairs have perfect classification performance (recall, precision, and F1-score all 1.0). I provide these candidate primers for free, under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.


    "My hope is that this blog post will help start a conversation about the design process for these critical diagnostic primers. Starting with these primers, and with input from other scientists, we can develop a set of candidate primers for COVID-19 that could be used by health agencies and private diagnostic kit manufacturers alike to not only generate more diagnostic kits, but better ones."

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  • DNAnexus


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    Ben Busby, PhD

    Novel Genomics Research Directions for COVID-19

    DNAnexus® has built the world’s most secure, trusted cloud platform and global network for scientific collaboration and accelerated discovery. We partner with customers to tackle the world’s most exciting opportunities in human health and beyond.


    To stimulate new genomics research ideas, Dr. Busby will present novel COVID-19 research directions - including a discussion on HLA typing for predisposition to COVID-19 severity and Interaction with phylogeny. 


    Ben has been a foundational part of our scientific community since the beginning and has extensively helped research teams find novel directions and connect with resources. We laud the breadth and depth of his genomics knowledge and resourcefulness.

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