Artificial Intelligence to Combat Antibiotic Resistant Bacteria

Artificial Intelligence to Combat Antibiotic Resistant Bacteria

Artificial Intelligence to Combat Antibiotic Resistant Bacteria – tools, techniques, models, scopes and challenges are discussed. Antibiotic resistance bacteria are one of the key research area of our Compassionate AI Lab. Dr. Amit Ray explains how artificial intelligence can be used in combating these superbugs. Antibiotic resistance bacteria is becoming world’s biggest health crisis. We discussed here multi-agent deep reinforcement learning models for predicting behavior of bacteria and phages in multi-drug environments.  We call this model as DeepCombat.

Artificial Intelligence to Combat Antibiotic Resistant Bacteria

Antibiotic resistant bacteria are bacteria that are not controlled or killed by antibiotics. They are able to survive and even multiply in the presence of an antibiotic.  These bacteria currently kill an estimated 700,000 people globally each year – a death toll which could rise to 10 million a year by 2050 if we don’t act [1]. The main difficulty is that the bacteria are changing fast. They changing faster than we can change the drugs in response.

 Artificial intelligence is showing alternative means of fighting these deadly infections and killer bacteria. Multi-drug-resistant bacterial infections annually result in millions of hospital days, billions in healthcare costs, and, most importantly, thousands of lives lost. Artificial Intelligence for healthcare is progressing at an exponential rate.  We are evaluating here, the role of artificial intelligence in fighting these superbugs.  Especially, the use of AI for intelligent Phage therapy.

Common Antibiotics 

Antibiotics are chemical compounds used to kill bacteria or inhibit the growth of infectious organisms (like Bacteria, protozoa). Alexander Fleming’s discovery of penicillin in 1928, which has rightfully been described as a “turning point in history”. After that, humans use hundreds of thousands of tons of antibiotics per year for medical, veterinary, and agricultural purposes. There are 5 generations of antibiotics. They are classified depending on their spectrum and bacteria killing abilities.

The 14 common antibiotics are; amikacin, amoxicillin/clavulanic acid, ampicillin, cephalexin, ceftiofur, cefuroxime, ciprofloxacin, clindamycin, cotrimoxazole, enrofloxacin, gentamicin, norfloxacin, ofloxacin and tetracycline.

Classification of Bacteria:

Bacteria are classified into two groups based on the structural differences in their cell walls: gram-negative and gram-positive bacteria.

Gram-negative bacteria have a thin membrane, which is nearly “bulletproof.” Gram-negative bacteria’s cell membrane is thin but difficult to penetrate. Because of this nearly “bulletproof” membrane, they are often resistant to antibiotics and other antibacterial interventions. Examples of Gram-negative bacteria include cholera, gonorrhea, Escherichia coli (E. coli),   Klebsiella pneumoniae, and Acinetobacter baumannii. These bacterial pathogens grow increasingly resistant to current antibiotics.

Gram-positive bacteria have a big, thick membrane. Gram-positive bacteria have a big, thick membrane but easy to penetrate. Examples of Gram-positive bacteria include Streptococcus, Staphylococcus, and Clostridium botulinum (botulism toxin).