AIMC Topic: Antibodies, Monoclonal

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Prediction of aggregation in monoclonal antibodies from molecular surface curvature.

Scientific reports
Protein aggregation is one of the key challenges in the biopharmaceutical industry as its control is crucial in achieving long-term stability and efficacy of biopharmaceuticals. Attempts have been made to develop regression models for predicting the ...

AlphaBind, a domain-specific model to predict and optimize antibody-antigen binding affinity.

mAbs
Antibodies are versatile therapeutic molecules that use combinatorial sequence diversity to cover a vast fitness landscape. Designing optimal antibody sequences, however, remains a major challenge. Recent advances in deep learning provide opportuniti...

Predicting the Effects of Charge Mutations on the Second Osmotic Virial Coefficient for Therapeutic Antibodies via Coarse-Grained Molecular Simulations and Deep Learning Methods.

Molecular pharmaceutics
The impact of various charge mutations on the second osmotic virial coefficient was examined for three model therapeutic monoclonal antibodies (MAbs) at representative formulation pH values by using coarse-grained (CG) molecular modeling. The wild-ty...

Patterns of calcitonin gene-related peptide monoclonal antibody use in people with migraine: Results of the OVERCOME (US) study.

Cephalalgia : an international journal of headache
BackgroundUnderstanding characteristics and reasons associated with using calcitonin gene-related peptide monoclonal antibodies (CGRP mAb) for migraine prevention may help clinicians individualize treatment plans and achieve better patient outcomes.M...

Computational design of therapeutic antibodies with improved developability: efficient traversal of binder landscapes and rescue of escape mutations.

mAbs
Developing therapeutic antibodies is a challenging endeavor, often requiring large-scale screening to produce initial binders, that still often require optimization for developability. We present a computational pipeline for the discovery and design ...

Recent advances in monoclonal antibody development for treatment of B-cell acute lymphoblastic leukemia.

Leukemia & lymphoma
Monoclonal antibody (mAb)-based therapies targeting CD19, CD20, and CD22 have revolutionized B-ALL treatment, offering precision and reduced systemic toxicity by engaging immune mechanisms to eliminate leukemic cells. This review synthesizes literatu...

Machine Learning for Predicting the Drug-to-Antibody Ratio (DAR) in the Synthesis of Antibody-Drug Conjugates (ADCs).

Journal of chemical information and modeling
The pharmaceutical industry faces challenges in developing efficient and cost-effective drug delivery systems. Among various applications, antibody-drug conjugates (ADCs) stand out by combining cytotoxic or bioactive agents with monoclonal antibodies...

How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience.

mAbs
Antibody discovery has been successful in designing and progressing molecules to the clinic and market based on largely empirical methods and human experience. The field is now transitioning from classical monospecific antibodies to innovative smart ...

A Novel Theranostic Strategy for Malignant Pulmonary Nodules by Targeted CECAM6 with Zr/I-Labeled Tinurilimab.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Lung adenocarcinoma (LUAD) constitutes a major cause of cancer-related fatalities worldwide. Early identification of malignant pulmonary nodules constitutes the most effective approach to reducing the mortality of LUAD. Despite the wide application o...