Biotechnology can turn out to be a fruitful asset in combating climate change. Here are a few ways how: Healthcare: The advent of oral vaccines and other genetically engineered vaccines will/have reduced the need for syringes, needles etc which are used to administer most vaccines currently. This siRead more
Biotechnology can turn out to be a fruitful asset in combating climate change. Here are a few ways how:
Healthcare: The advent of oral vaccines and other genetically engineered vaccines will/have reduced the need for syringes, needles etc which are used to administer most vaccines currently. This significantly decreases the biohazardous waste produced.
Agriculture: The nutritive value of soil has considerably declined and the production of genetically modified crops like golden rice, flavr-savr tomato and round-ready soybean has helped not only enhance the nutrition per square of land used but made them more sustainable to stay in the market for longer durations downplaying the constant need to produce food that requires a lot of water.
Infrastructure: Urban heat islands are a major problem in cities owing to the heat waves and building materials used. Biotechnology in combination with material science can help manufacture raw materials used in construction enabling better management of temperatures.
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AI and ML are modifying the biotech sector, especially the drug development sector. These processes inspect big data sets quickly and accurately, thus identifying patterns and potential drug candidates more rapidly than conventional techniques. Here is a brief summary: 1. Forecasting Models: ArtificRead more
AI and ML are modifying the biotech sector, especially the drug development sector. These processes inspect big data sets quickly and accurately, thus identifying patterns and potential drug candidates more rapidly than conventional techniques. Here is a brief summary:
1. Forecasting Models: Artificial intelligence algorithms anticipate the interactions between various compounds and biological targets, aiding in the early identification of potential drug candidates during the research phase.
2. Analyzing Data: Machine learning analyses large volumes of biological and chemical data, revealing connections and information that human researchers may overlook.
3. AI conducts virtual screening of chemical libraries, decreasing the time and expenses needed for experimental testing of each compound.
4. Drug Repurposing: Through the analysis of current medications and their impacts on different illnesses, artificial intelligence can discover fresh therapeutic applications, hastening the drug development process.
5. Tailored Treatment: Artificial intelligence-based treatment is designed to suit individual patients through the analysis of genetic, environmental and lifestyle information thereby making it more effective and reducing the risk of side effects.
In conclusion, by generally enhancing the efficacy and accuracy of drug discovery, AI and ML also shorten the period taken before new medicines are introduced into the market at lower costs and higher efficiency.
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