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Biological Products

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Real-World Screening Data for Liver Fibrosis in Psoriasis Patients Treated with Biologics.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is positively associated with the prevalence and severity of psoriasis. The fibrosis-4 (FIB-4) index was developed to predict significant liver fibrosis. Using the FIB-4 ind...

Explainable deep learning enhances robust and reliable real-time monitoring of a chromatographic protein A capture step.

Biotechnology journal
The application of model-based real-time monitoring in biopharmaceutical production is a major step toward quality-by-design and the fundament for model predictive control. Data-driven models have proven to be a viable option to model bioprocesses. I...

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance.

JCO clinical cancer informatics
PURPOSE: To apply deep learning algorithms to histopathology images, construct image-based subtypes independent of known clinical and molecular classifications for glioblastoma, and produce novel insights into molecular and immune characteristics of ...

New peperomin and polyketides from dichloromethane extract of Peperomia blanda Jack. (Kunth).

Tropical biomedicine
Much of the new research and investigation in pharmacy sciences are concerned with developing therapeutic agents, and identifying and finding new drugs with their chemical structure to treat different human diseases such as infectious diseases from n...

[Bridge between Total Synthesis of Bioactive Natural Products and Development of Drug Leads].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Although natural products are rich sources for drug discovery, only a small percentage of natural products themselves have been approved for clinical use, thus it is necessary to modulate various properties, such as efficacy, toxicity, and metabolic ...

The application potential of machine learning and genomics for understanding natural product diversity, chemistry, and therapeutic translatability.

Natural product reports
Covering: up to the end of 2020. The machine learning field can be defined as the study and application of algorithms that perform classification and prediction tasks through pattern recognition instead of explicitly defined rules. Among other areas,...

Machine learning approaches for elucidating the biological effects of natural products.

Natural product reports
Covering: 2000 to 2020 Machine learning (ML) is an efficient tool for the prediction of bioactivity and the study of structure-activity relationships. Over the past decade, an emerging trend for combining these approaches with the study of natural pr...

Predicting Secukinumab Fast-Responder Profile in Psoriatic Patients: Advanced Application of Artificial-Neural-Networks (ANNs).

Journal of drugs in dermatology : JDD
BACKGROUND: Drug resistance to biologics in psoriasis therapy can occur – it may be acquired during a treatment or else present itself from the beginning. To date, no biomarkers are known that may reliably guide clinicians in predicting respons...

Predicting Corticosteroid-Free Biologic Remission with Vedolizumab in Crohn's Disease.

Inflammatory bowel diseases
BACKGROUND AND AIMS: Vedolizumab (VDZ) is effective for Crohn's disease (CD) but costly and is slow to produce remission. Early knowledge of whether vedolizumab is likely to succeed is valuable for physicians, patients, and insurers.