Artificial Intelligence (AI) has revolutionized the formulation and development of modern pharmaceuticals, significantly reducing the time and cost associated with drug development. AI's ability to analyze vast amounts of data and identify patterns that human researchers might miss is a key advantage. Tools such as Artificial Neural Networks (ANN), fuzzy logic, neuro-fuzzy logic, and genetic algorithms are used to optimize drug design, develop formulations, and streamline clinical trials. AI can forecast solubility, stability, and bioavailability of drug candidates, improving the likelihood of successful clinical trials. It also aids in designing clinical trials by identifying patient populations most likely to benefit from treatments and monitoring patients during trials to detect adverse effects and adjust dosages. AI is applied in various stages of the pharmaceutical product life cycle, including drug discovery, optimization, formulation development, characterization, quality testing, marketing, and post-marketing surveillance. It supports decision-making, enables rational drug design, and enhances personalized medication. AI can predict the efficacy and safety of drugs, reduce bias and human interference, and address inefficiencies in traditional drug development approaches. In drug formulation, AI helps optimize formulations for controlled-release, immediate-release, and hard gelatin capsule shells. It also addresses issues such as low solubility, stability, and bioavailability. AI is used in the development of solid dispersions, emulsions, microemulsions, nanoemulsions, and self-emulsifying drug delivery systems (SEDDS). It enhances the efficacy and safety of treatments by optimizing drug delivery methods. AI is also used in quality control and assurance, product development, and drug synergism and antagonism prediction. It aids in the development of nanorobots for drug delivery and nanomedicine, which merge nanotechnology and drugs to treat complex diseases. AI platforms can predict drugs' on- and off-target effects and in vivo safety profiles, reducing attrition rates and accelerating drug development. The future prospects of AI in pharmaceutical formulation and development are promising. As AI continues to evolve, it is expected to play an even more significant role in drug development, enabling researchers to identify new drug targets, interactions, and patient populations. AI will also facilitate the development of more personalized and effective treatments, leading to more efficient and targeted drug development and personalized medicine.Artificial Intelligence (AI) has revolutionized the formulation and development of modern pharmaceuticals, significantly reducing the time and cost associated with drug development. AI's ability to analyze vast amounts of data and identify patterns that human researchers might miss is a key advantage. Tools such as Artificial Neural Networks (ANN), fuzzy logic, neuro-fuzzy logic, and genetic algorithms are used to optimize drug design, develop formulations, and streamline clinical trials. AI can forecast solubility, stability, and bioavailability of drug candidates, improving the likelihood of successful clinical trials. It also aids in designing clinical trials by identifying patient populations most likely to benefit from treatments and monitoring patients during trials to detect adverse effects and adjust dosages. AI is applied in various stages of the pharmaceutical product life cycle, including drug discovery, optimization, formulation development, characterization, quality testing, marketing, and post-marketing surveillance. It supports decision-making, enables rational drug design, and enhances personalized medication. AI can predict the efficacy and safety of drugs, reduce bias and human interference, and address inefficiencies in traditional drug development approaches. In drug formulation, AI helps optimize formulations for controlled-release, immediate-release, and hard gelatin capsule shells. It also addresses issues such as low solubility, stability, and bioavailability. AI is used in the development of solid dispersions, emulsions, microemulsions, nanoemulsions, and self-emulsifying drug delivery systems (SEDDS). It enhances the efficacy and safety of treatments by optimizing drug delivery methods. AI is also used in quality control and assurance, product development, and drug synergism and antagonism prediction. It aids in the development of nanorobots for drug delivery and nanomedicine, which merge nanotechnology and drugs to treat complex diseases. AI platforms can predict drugs' on- and off-target effects and in vivo safety profiles, reducing attrition rates and accelerating drug development. The future prospects of AI in pharmaceutical formulation and development are promising. As AI continues to evolve, it is expected to play an even more significant role in drug development, enabling researchers to identify new drug targets, interactions, and patient populations. AI will also facilitate the development of more personalized and effective treatments, leading to more efficient and targeted drug development and personalized medicine.