As governments all over the world strive to prevent the COVID-19 contagion and take care of all those affected through therapeutic and preventive measures, the brightest minds in medical science have been fighting their own battle against the virus to find possible drugs and treatment for countering the disease.
Discovery of drugs or vaccines for a novel virus is itself a time-consuming and complex process, not to mention expensive as well. Understanding the complexity of the human physiology and the activity of the virus, how it replicates and attacks the human cells, and all the other aspects have an important role to play in drug discovery, that demands in-depth analysis followed by clinical trials. When finding the probable cure for a pandemic causing virus, the task becomes more challenging as the researchers are racing against time.
In the ongoing fight against the novel coronavirus disease, luckily, we have the assistance of new-age technologies like machine learning (ML) and artificial intelligence (AI), which has can streamline and speed up the process of drug discovery and development.
All around the world, multiple use cases of AI have come to light, that is helping the researchers in tracking the latest findings, and supporting them in creating novel compounds for possible drugs and vaccines.
Artificial Intelligence for Drug Discovery
Over the years, especially in the recent ones, the pharma and healthcare industry has seen optimistic adoption of artificial intelligence for streamlining the healthcare machinery and for the development of new treatments and drugs. According to the market survey report, the global AI in the drug market is expected to reach $1,434 million by 2024 from $259 million in 2019, at a 40.8 percent CAGR (2019-2024).
While the health industry was already dabbling in AI, the COVID-19 attack has accelerated the adoption process, with artificial intelligence becoming the key contributor in the research for drug discovery. Here’s a couple of ways that technology is helping:
- Information Engines
The discovery of a drug goes through multiple stages and only gets an approval after clinical trials. Before that, the researcher has also to figure out the exact dose and delivery method of the drug for effective treatment.
Also read: The Role of Blockchain in Shaping the Post-Pandemic World
Information engines are fundamental applications for drug discovery since these serve as an information aggregator and the synthesizer layer, which can offer the basis of further insights and prescriptive analysis of the drug.
Researchers gain access to substantial information, which they need to update and aggregate as they move ahead in their work. AI-backed information engines make it an easy process for them. It also helps in pulling out the most relevant data needed for a specific study.
There is a broad spectrum of information that is fed into the information engines, the sources of which are equally diverse. Relevant information such as disease information, medical records, published scientific research papers, medical journals, biomedical data, ligand information, credible history of clinical trials, patent information on drugs and compounds being tested by pharma companies, genomic sequencing data, cohort data, radiology imaging data, society, and environmental data are all integrated into the advanced information engines.
These applications also play an important role during the clinical trials. They help in reducing the cost and augment the process, thus increasing the chance of success. Information engines, help the researchers to analyze and synthesize substantial amounts of information, which simplifies the process of understanding the disease behavior.
The ones involved in drug discovery and clinical trials are also able to find potential candidates, as the medical records are fed into the system as well.
- AI for Drug Design and Development
Drug design involves crafting the molecular design of the compound for medicines and vaccines. It is an intricate process, that can be optimized with the help of AI-based drug design applications.
These applications gather all data and information from the information engines and help in the creation of new drugs, followed by its optimization and validation or repurpose the existing drugs with mild variations for a novel treatment.
In the initial stage, the machine learning algorithm will predict the potential targets of the virus. It is followed by an artificial intelligence triage ordering targets, that are based on safety, chemical opportunity and drug availability. It is then presented and ranked with the most relevant targets.
All the initial drug development information and data is entered into the AI-based drug design application, which then optimizes the compound with the relevant properties before synthesizing it. The data that is generated during the experiment, can be further fed into the application for added optimization and analysis of the compound.
In the case of repurposing, the existing drug, it’s compound and the treatment effects are compared with the novel disease, to find similar patterns and targets. Drug repurposing is a great way to generate revenue from already marketed pharmaceuticals and it is easy to develop and send for mass production as well. While discovering and developing a new compound is both expensive and time taking, repurposed drugs showcase effective results in times of crisis.
AI for COVID-19
It’s been some time that both AI developers and pharmaceutical companies have been trying to collaborate in hopes of furthering medical and technological breakthroughs, not to mention turn the investments into revenue channels.
The COVID-19 invasion during such a time comes as a scope of a trial run for AI companies, where they showcase the value of the technology, by helping the world fighting the pandemic.
As of yet, AI applications have been used to find the protein structures linked to the novel coronavirus, which is essential to developing a drug or a vaccine. As it awaits experimental verification, AI has scope to further contribute to the ongoing research.
AI algorithms are been used by pharma companies in China and Hong Kong (Insilico Medicine) to create new molecular structures, that can potentially prevent the virus from replicating. The application used the existing data on similar viruses like SARS and presented six new molecular structures for COVID-19 treatment.
A German company has designed a new molecule with a high binding capacity to target the protein attached to the coronavirus. These AI initiative examples that keep surfacing regularly, are just the tip of the iceberg. Experts are predicting that the latest pandemic and the united effort of the world to discover a vaccine or drug will revolutionize both the medical and AI industry, paving a post-pandemic future of AI-backed advanced medical treatments and drug developments.
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