Evaluation of factors important in modeling plasma concentrations of tetracycline hydrochloride administered in water in swine

Influence of water quality and pollution on broiler's performance, vaccine and antibiotic efficiencies

Good water quality for livestock is critical for preserving animal health, ensuring the quality of animal products, supplying safe food, and increasing food production economics. Higher water levels of toxic compounds than permitted can impair meat, fat, eggs, and milk production, lower fertility, and represent public health hazards. Water picks up pollutants from its surroundings and those caused by animal and human activities. Many physicochemical parameters were used to ensure water quality, including pH, salt, taste, color, alkalinity, odor, and hardness. Water quality, directly and indirectly, impacts livestock performance and, thus, the poultry industry. Employing drinking water as a carrier of drugs still faces substantial barriers. The effectiveness of vaccinations and drugs is affected by inadequate water quality. Furthermore, contaminated water and poor nutrition negatively affect broiler chicken immunity, survival, and production. Antibiotics are widely utilized in poultry production to preserve animal health and growth. They can eliminate harmful bacteria in the gut, reduce the load on the immune system, optimize the digestive system, and boost growth performance. However, the abuse of antibiotics in animal agriculture has resulted in antibiotic-resistant infections threatening people and animals. As a result of its positive impact on the metabolome and gut microbiome, the natural antimicrobial combination could be used as an alternative; improving broiler chicken growth performance without negatively affecting the environment is currently paramount.

A framework for meta-analysis of veterinary drug pharmacokinetic data using mixed effect modeling

Combining data from available studies is a useful approach to interpret the overwhelming amount of data generated in medical research from multiple studies. Paradoxically, in veterinary medicine, lack of data requires integrating available data to make meaningful population inferences. Nonlinear mixed-effects modeling is a useful tool to apply meta-analysis to diverse pharmacokinetic (PK) studies of veterinary drugs. This review provides a summary of the characteristics of PK data of veterinary drugs and how integration of these data may differ from human PK studies. The limits of meta-analysis include the sophistication of data mining, and generation of misleading results caused by biased or poor quality data. The overriding strength of meta-analysis applied to this field is that robust statistical analysis of the diverse sparse data sets inherent to veterinary medicine applications can be accomplished, thereby allowing population inferences to be made.