Antimicrobial resistance (AMR) occurs when microbes evolve mechanisms that protect them from the effects of antimicrobials (drugs used to treat infections).
All classes of microbes can evolve resistance where the drugs are no longer effective.
Fungi evolve antifungal resistance, viruses evolve antiviral resistance, protozoa evolve antiprotozoal resistance, and bacteria evolve antibiotic resistance.
Use of AI
Where existing libraries also fall short, some AI-driven computer programs can also predict the structures of potential drug molecules.
Chemists can synthesise them from scratch or one can pick existing molecules with similar structures and modify them.
Works are going on with AI-based companies to help with computational drug discovery, and plan to work with the pharmaceutical industry to synthesise them
Use of AI
Some recommend drug companies add the newly discovered targets to their to-be-tested lists.
These companies already have the capacity to conduct high-throughput screening — a process in which researchers check the suitability of thousands or even millions of molecules in parallel.
Such molecules are more logistically and financially feasible than one scientist testing a handful of drug targets.
The Process and Challenge
Once a suitable group of molecules has been identified, they will have to be tested procedurally for safety and efficacy.
First in a cell culture model and then in experimental animal models, researchers check if the inhibitors selectively work against pathogens (rather than against human cells).
Today, many startups also work as contract research labs and perform such tests.
After this begin the clinical trials, which are closely regulated to ensure they are ethically conducted and produce data uncompromised by any bias.
The Process and Challenge
If the trials’ results surpass a predetermined threshold of success, regulatory authorities approve the drugs for the market
This road between identifying new drug targets and actually having drugs against those targets is long but necessary.
It requires expertise of many kinds to ease the process.
The Process and Challenge
Developing tools such as molecular docking simulations, AI-driven drug discovery, and chemical libraries all exemplify collaborations between infectious disease biologists, structural biologists, computational biologists, chemists, and various research institutions motivated by a common cause and, of course, sufficient funding.
This network also has to expand to include startups and the industry at large.
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