A Corona disease has now been confirmed pandemic as well as new treatments are immediately needed as we go into a phase beyond suppression. Emerging new drugs from scratch is a lengthy process, so unrealistic to face the instant global challenge. Drug repurposing is a developing strategy where existing medicines, having already been tested safe in humans, are reorganized to battle difficult-to-treat diseases. Combined blends of repurposed drugs could be very effective, the urgent question now being which combination.
The epidemic of the unique coronavirus disease, COVID-19, triggered through the new coronavirus 2019-nCoV that is currently publically labeled as severe critical respiratory syndrome linked to coronavirus SARS-CoV-2, signifies a pandemic threat to global public health. Although the epicenter of the COVID-19 outbreak in December of 2019 was located in Wuhan, China, this disease has spread to more than 110 countries with over 2 million confirmed cases and over 1.7 lacs confirmed deaths worldwide as of April 21, 2020. What are practical approaches to determine latent candidate treatments to battle severe critical respiratory syndrome coronavirus 2 (SARS-CoV-2)? Here we take a snapshot look at the strategy of drug repurposing-that promises to identify antiviral agents for the novel coronavirus disease in a time-critical fashion. We also offer a perspective regarding scope of AI against battle with COVID-19.
Drug Repurposing (Broad Spectrum Antiviral Agent)
Andersen et al. have freshly abridged 31 possible applicants for COVID-19 in a extremely available record of 120 experimental, investigational as well as accepted agents. Both lopinavir/ritonavir is a drug combination targeting viral protease approved for the indications HIV. They are currently being considered in different combinations with Arbidol in a Phase IV clinical trial for pneumonia associated with COVID-19.
During Phase III level, remdesivir, a viral RNA-dependent RNA polymerase inhibitor, is below examination for mild as well as moderate SARS-COV-2. Remdesivir has activity in preclinical studies against the species of coronaviridae implicated in SARS-COV as well as Middle East respiratory syndrome (MERS-COV). Other Phase III agents being evaluated in combination therapy for viral pneumonia interestingly include the antimalarial hydroxychloroquine, based on promising in vitro data. Finally, preclinical studies of ribavirin (ribonucleic analog) have shown in vitro activity against SARS-CoV-2.
Barcitinib was projected because of its anti-inflammatory outcome as well as possible capability to diminish viral entry. Favipiravir, a purine nucleoside leading to inaccurate viral RNA synthesis has recently been approved for a clinical trial as a drug to treat COVID-19 (2, 3 and 4).
Use of Artificial intelligence for COVID-19:
Around six areas where AI can subsidize to the contest against COVID-19: i) early warnings as well as alerts, ii) tracking as well as prediction, iii) data dashboards, iv) diagnosis as well as prognosis, v) treatments, and cures, and vi) social control (5).
Artificial intelligence may have been overestimated, but when it arises to medicine, it previously has a established track record. The researcher group based from Scripps research institute in California claimed that they are first to put an AI-discovered drug into human trial, is trawling through 15,000 drugs.
Dr. David Brown has mentioned its AI system established to discover drugs for rare diseases. According to him, AI system is divided into 3 parts that:
- Trawl through all the existing literature connecting to the disease
- Study the DNA as well as structure of the virus
- Consider the suitability of various drugs
Peoples working in area of AI drug discovery, there are two options as soon as it arises to coronavirus:
- Find a completely new drug, wait a couple of years for it to be permitted as safe for use.
- Repurpose existing drugs.
Chinese company Alibaba claims to have developed an AI test that can accurately detect coronavirus within 20 seconds with 96% accuracy.
Fundamental Need of AI:
Dr.Darzi, director of the Institute of Global Health Innovation, at Imperial College addressed that AI remains one of our solidest trails to realize a noticeable solution then there is a essential need for high quality, large and clean data sets. Today’s date, all information regarding drug discovery data has been siloed in individual companies such as big pharma or lost in the intellectual property and old lab space within universities.
There is need to collect disparate drug discovery data sources to allow AI researchers to apply their novel machine-learning techniques to generate new treatments for Covid-19 as soon as possible. A worldwide health emergency of this scale calls for a brave, global reply at the governmental as well as political levels. Therefore, the regulatory community must act fast to minimize any financial hurdles implicating private industry and update guidelines for drug licensure through repurposing with help of AI and machine learning tools against battle with global pandemic.
ARPB Blogger ID: ARPBGZ255
