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Shivom Launches FREE Informatics – Secure Health Data Sharing Solutions to Organisations Studying COVID-19.
LONDON, UNITED KINGDOM - May 29, 2020 -
Shivom Ventures Limited Shivom today announced the startup will be playing its part in combating the deadly coronavirus disease by offering researchers and pharmaceutical companies a 1-year free subscription to interrogate both viral and human genomes separately from RAW sequencing data. The newly released platform, Shivom.io connects data consumers with data custodians to help advance biomedical research. Anyone can use the Shivom platform to share multi-omics data securely and additionally has built comprehensive cloud-informatics solutions offering a library of multi-omics Covid-19 pipelines and aggregation analysis pipelines such as GWAS, PheWAS, PRS, Meta-GWAS and more. The platforms proprietary design enables global data sharing and interrogation through its secure-permission and consent mechanism which allows researchers to analyse data without being given access to the RAW data files.
This past couple of months have been tough on many and with the troubling news from the WHO last week that a total of 5.1M cases and 333K deaths recorded globally it is looking grim. However, new startup Shivom has decided to play its part in combating the deadly disease by launching a new solution which enables researchers, pharmaceutical companies and NGOs the ability to utilise Shivoms cloud-informatics and secure omics-sharing solutions completely free for one year in order to help develop a vaccine for coronavirus. To gain access to their offer, the company has issued a coupon collaboration which can be redeemed for a Starter account following signing up here.
By offering our 1-click access big data platform for free we can enable a large number of researchers with the tools needed to develop a vaccine and remove the boundaries and complexities when it comes to data-sharing between entities and jurisdictions. Now more than ever is a time that we need to come together and collaborate in order to come up with a solution. I believe the answer is to collaborate through consortium building rather than siloed data and be front runners to the vaccine. The effect goes beyond the patients and families of loved ones who have passed from the disease, but also to the people who have lost their jobs and way of being from it. Nate Raine, Chief Operating Officer at Shivom.
This pandemic has cost half a million deaths worldwide and it continues to rise daily. It is predicted that a second wave will hit later in 2020 and there are currently no established therapies or vaccines that are effective in combating this deadly disease.
Although we are getting better at understanding the disease biology of COVID-19 each day, we are still limited in our understanding. With a host of different drugs and vaccines in trials for COVID-19, it is critical to identify the right vaccine or therapeutic intervention for the right individual. Whilst it is important that the drug is beneficial to the individual it is also necessary to mitigate the risk of adverse drug reactions (ADR). Currently, ADR costs the UKs NHS £2 billion per year and accounts for 6-7% of hospital admission in the UK. This can be reduced by pharma/biotech calculating genetic risk scores from clinical trialists and modelling against their trial data outcomes. This allows for a safer and cost-efficient approach in stratifying individuals for the most optimal intervention once these interventions arrive in clinics and hospitals.
Our platform provides the necessary tools to prepare and analyse sequencing data to give these insights. We provide a host of pipelines, that confirms the presence SARS-CoV-2, calls and identifies variants in the human genome and algorithms that can model the genetic summary statistics to predict risk score of ADR to any given intervention, said VP, Product Ibrahim Farah.
According to Ibrahim, the curated set of pipelines allow scientists to quickly characterise the novel coronavirus by:
Identifying SARS-CoV-2 presence within a sample;
Distinguish variant-level differences between samples;
Quantify the amount of SARS-CoV present in each sample;
Detect susceptibility, symptomatic/asymptomatic status and disease progression is due to human genome variation
WHY IT MATTERS
Science is moving at a phenomenal pace against COVID-19, but it is still too slow to match the momentum of the SARS-CoV-2 coronavirus.
The SARS-CoV2 pandemic is the black swan of 2020 and everyone has been impacted. It is evident that only unprecedented global collaboration and access to innovative technical infrastructure can remove obstacles to the free flow of research data, ideas, and thus accelerate the pace of research critical to combating COVID-19.
Coordination between the multiple COVID-19 research initiatives needs to be improved toward the public interest, shifting the culture to one where sharing is the norm. While clinical data about COVID-19 is widely produced, most data is dispersed and not sufficiently findable, accessible, and reusable; particularly across borders under current data protection frameworks. Only by building and maintaining trust between data custodians and having access to algorithms which could use the data to answer specific research questions, that can guarantee an impact on the pandemic, as well as the preparedness for any future emergencies. said Dr. Axel Schumacher, President at Shivom.
Just this week, the OECD published their COVID-19 policy briefs, detailing Why open science is critical to combatting COVID-19. The key message was to strengthen the contribution of open science to the pandemic response ensuring sustainable data sharing, and mechanisms for accessing data across borders. Shivom can assist the global research community to achieve these goals by using our platforms state-of-the-art data analytics. With virus and anonymized host genomic data available on the platform, the research community will create new opportunities to bridge the gap between public health, pharma, and academia, thus enabling even the novice of users with the ability to explore, contribute and interrogate the virus as well.
Sharing, finding, and analyzing various precision medicine data (i.e. genetic, epigenetic, medical records, outcome, etc.) with the Shivom Platform will help to generate the following scientific and public health outcomes:
A better understanding of genes that could be correlated with SARS-CoV susceptibility and the efficiency of detection tests;
Further insight into factors that could be correlated with the development of toxicity against current drug treatment modalities for COVID-19 affected patients;
Contribution to public health preparedness and response in the context of the ongoing pandemic of COVID-19 and future viral public health emergencies;
Enabling much faster development and availability of vaccines, therapeutics and/or diagnostics to be used in the clinical management of patients
The COVID-19 pandemic requires various health-related sciences divisions work cohesively together with a shared purpose and acknowledge that the public health crisis surpasses our individual public and private interests. Although there are already some data initiatives, those consortia still produce further data silos. Shivom can help to rapidly channel the efforts of all those initiatives. For big data approaches to thrive, historical barriers dividing research groups and institutions need to be broken down and a new era of open, collaborative, and data-driven science needs to be ushered in.
Shivom provides 1-click access to genomic data and insights. The end-to-end cloud operating system enables computation and analysis to Omics data, accelerating drug discovery and delivering novel insights to personalised medicine. Users are able to gain easy access to genomic data and the ability to run various bioinformatics & AI tools in one environment.
Headquartered in London, UK, Shivoms mission is to build the worlds largest genetic marketplace. Shivoms ecosystem of partners and customers spans 10 countries including two active European pilot projects with H2020.
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