Journal of Pharmaceutical and BioTech Industry

Medicine is accelerating rapidly, offering the advantages of site-specific delivery, minimized side effects, and improved treatment outcomes. A diverse array of chronic diseases, such as cancer, diabetes, asthma, myocardial infarction, and Alzheimer’s disease, are often accompanied by severe adverse effects and limited specificity, necessitating concentrated attention on targeted therapies. Recent advancements in molecular profiling and understanding of target pathways have enabled the identification of specific biomarkers and gene targets. These advancements have led to the development of targeted therapies that focus on the specific molecular alterations responsible for disease progression. Such therapies offer a more personalized and effective approach to treatment. This review focuses on the benefits of targeted therapies compared to traditional therapeutics and provides an overview of currently available targeted therapies for chronic diseases. By highlighting these advancements, the review aims to illustrate the progress in disease treatment towards more personalized approaches. The goal is to underscore how targeted therapies have evolved and how they represent a significant shift towards personalized therapy.

Lecythidaceae species are known worldwide for their ability to produce edible nuts of high nutritional value, such as Brazil nuts, and are also used in traditional medicine in countries across America, Asia, and Africa. The potential of these species has aroused interest in their chemical composition, nutritional properties, and biological activities, with emphasis on anti-inflammatory and antinociceptive actions. The objective of this review was to summarize data regarding the anti-inflammatory and antinociceptive activities of Lecythidaceae species, identify the most promising bioactive agents, and elucidate their potential mechanisms of action. This integrative review was conducted by comprehensively searching the main electronic databases for scientific articles, with no restriction on publication date, that were available in full. Based on this survey, thirty-four articles were identified, covering twelve Lecythidaceae species with anti-inflammatory and antinociceptive actions evaluated in in vitro and in vivo models and randomized clinical trials. Studies encompass extracts, fractions, nuts, and isolated compounds, among which the extracts and fractions of Barringtonia angusta Kurz, Couroupita guianensis Aubl., Lecythis pisonis Cambess., and Petersianthus macrocarpus (P. Beauv.) Liben demonstrated potent inhibition of inflammatory mediators through suppression of gene expression in vitro and in vivo, acting via blockade of the nuclear factor kappa-light-chain-enhancer of activated B cells (KN-κB) signaling pathway. This finding highlights a relevant molecular mechanism by which Lecythidaceae species may exert their anti-inflammatory potential and supports further studies focused on isolating active fractions and elucidating possible synergistic effects. Ethnopharmacological and chemical composition data are also presented and discussed within the scope of their biological applications, highlighting the therapeutic potential of Lecythidaceae species and identifying promising candidates for future development of novel anti-inflammatory phytopharmaceuticals.

The design and development of a robust and consistent manufacturing process for monoclonal antibodies (mAbs), augmented by advanced process analytics capabilities, is a key current focus area in the pharmaceutical industry. In this work, we describe the development and operationalization of multivariate statistical process monitoring (MSPM), a data-driven modelling approach, to monitor biopharmaceutical manufacturing processes. This approach helps in understanding the correlations between the various variables and is used for the detection of the deviations and anomalies that may indicate abnormalities or changes in the process compared to the historical dataspace. Therefore, MSPM enables early fault detection with a scope for preventative intervention and corrective actions. In this work, we will additionally cover the value of in silico data in the development of MSPM models, principal component analysis (PCA), and batch modelling methods, as well as refining and validating the models in real time.