Artificial Intelligence (AI) focuses in producing intelligent modelling, which helps in imagining knowledge, cracking problems and decision making. Recently, AI plays an important role in various fields of pharmacy like drug discovery, drug delivery formulation development, polypharmacology, hospital pharmacy, etc. In drug discovery and drug delivery formulation development, various Artificial Neural Networks (ANNs) like Deep Neural Networks (DNNs) or Recurrent Neural Networks (RNNs) are being employed. Several implementations of drug discovery have currently been analysed and supported the power of the technology in quantitative structure-property relationship (QSPR) or quantitative structure-activity relationship (QSAR). In addition, de novo design promotes the invention of significantly newer drug molecules with regard to desired/optimal qualities. In the current review article, the uses of AI in pharmacy, especially in drug discovery, drug delivery formulation development, polypharmacology and hospital pharmacy are discussed.

Understanding of variations in the course and source of abdominal arteries is crucial for any surgical intervention in the peritoneal space. Intricate surgeries of the upper abdominal region, such as hepato-biliary, pancreatic, gastric and splenic surgeries, require precise knowledge of regular anatomy and different variations related to celiac trunk and hepatic artery. In addition, information about the origin of inferior phrenic artery is important in conditions such as hepatocellular carcinoma and gastroesophageal bleeding management. The present study gives an account of anatomical variations in origin and branching pattern of celiac trunk and hepatic artery by the use of CT (computed tomographic) angiography. The study was performed on 110 (66 females and 44 males) patients in a north Indian population. Results unraveled the most common celiac trunk variation as hepatosplenic trunk with left gastric artery, which was observed in 60% of cases, more common in females than in males. Gastrosplenic and hepato-gastric trunk could be seen in 4.55% and 1.82% cases respectively. Gastrosplenic trunk was more commonly found in females, whereas hepato-gastric trunk was more common in males. A gastrosplenic trunk, along with the hepato-mesenteric trunk, was observed in 1.82% cases and was more common in males. A celiacomesenteric trunk, in which the celiac trunk and superior mesenteric artery originated as a common trunk from the aorta, was seen only in 0.91% of cases, and exhibited an origin of right and left inferior phrenic artery from the left gastric artery. The most common variation of hepatic artery, in which the right hepatic artery was replaced and originated from the superior mesenteric artery, was observed in 3.64%, cases with a more common occurrence in males. In 1.82% cases, the left hepatic artery was replaced and originated from the left gastric artery, which was observed only in females. Common hepatic artery originated from the superior mesenteric artery, as observed in 1.82% cases, with slightly higher occurrence in males. These findings not only add to the existing knowledge apart from giving an overview of variations in north Indian population, but also give an account of their correlation with gender. The present study will prove to be important for various surgeries of the upper abdominal region.

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The anthropometry of the proximal femur holds great clinical significance in designing implants and prostheses for proximal femoral fractures and hip joint arthroplasties. Surgical fixation with a properly matched prosthesis plays a crucial role in improving long-term treatment outcomes and preventing postoperative complications such as osteolysis with aseptic loosening and increased load. The femur is also one of the most commonest used bones for stature estimation. Often during forensic investigations, only fragmented remains of femur are found available from which femoral length is estimated by application of linear regression equations. The estimated femoral length thus obtained is used for stature estimation of the unidentified individual. This study has measured nine bony parameters from the proximal femur in a total of 96 dry femora. These measurements include the vertical head diameter, neck diameter, neck thickness, neck length, neck shaft angle, the transverse diameter of the fovea, longitudinal diameter of the fovea, foveal depth, and the intertrochanteric line length. In addition, the total length of the femur was also measured. The results were tabulated and statistically analyzed using SPSS software, version 25. The mean femoral head diameter was observed to be 41.59±3.25 mm, mean foveal depth was found to be 2.95±0.75 mm, mean foveal transverse and longitudinal diameters were observed to be 11.38±2.35 mm and 15.94±3.37 mm, respectively. The mean neck diameter was 29.45±3.33 mm. Mean neck length and neck thickness were observed to be 36.06±4.94 mm and 27.61±2.71 mm, respectively. Neck shaft angle was noted to range from 109° to 128°, with a mean of 119.08°±5.18°. The mean length of the inter-trochanteric line was measured to be 41.92±3.9 mm. The mean femoral length was observed to be 42.11±2.91 cm. Significant positive correlations were found between the various measured proximal morphometric parameters of the femur. The length of the femur showed a maximum positive correlation with the vertical head diameter, followed by the neck diameter, thickness, and foveal depth. The findings of this study can throw further light on the existing data. They can serve as a guideline for designing better-matched prostheses and implants for hip surgeries in the eastern Uttar Pradesh population.

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