mAbs

Papers
(The H4-Index of mAbs is 26. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)
ArticleCitations
Antibodies to watch in 2022238
Antibodies to watch in 2021235
Antibodies to watch in 2023114
Targeting cancer with antibody-drug conjugates: Promises and challenges87
BioPhi: A platform for antibody design, humanization, and humanness evaluation based on natural antibody repertoires and deep learning58
Simlukafusp alfa (FAP-IL2v) immunocytokine is a versatile combination partner for cancer immunotherapy53
Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies51
501Y.V2 and 501Y.V3 variants of SARS-CoV-2 lose binding to bamlanivimab in vitro49
Developments and opportunities in continuous biopharmaceutical manufacturing40
In silico proof of principle of machine learning-based antibody design at unconstrained scale37
Fc galactosylation follows consecutive reaction kinetics and enhances immunoglobulin G hexamerization for complement activation37
Ten years in the making: application of CrossMab technology for the development of therapeutic bispecific antibodies and antibody fusion proteins36
Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics36
Coming together at the hinges: Therapeutic prospects of IgG334
Polyreactivity and polyspecificity in therapeutic antibody development: risk factors for failure in preclinical and clinical development campaigns34
A computational method for immune repertoire mining that identifies novel binders from different clonotypes, demonstrated by identifying anti-pertussis toxoid antibodies32
Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods32
One size does not fit all: navigating the multi-dimensional space to optimize T-cell engaging protein therapeutics31
Cadonilimab, a tetravalent PD-1/CTLA-4 bispecific antibody with trans-binding and enhanced target binding avidity31
Preclinical evaluation of AFM24, a novel CD16A-specific innate immune cell engager targeting EGFR-positive tumors31
Host cell protein profiling of commercial therapeutic protein drugs as a benchmark for monoclonal antibody-based therapeutic protein development30
Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics29
Calculation of therapeutic antibody viscosity with coarse-grained models, hydrodynamic calculations and machine learning-based parameters28
Effect of variable domain charge on in vitro and in vivo disposition of monoclonal antibodies27
Identifying biophysical assays and in silico properties that enrich for slow clearance in clinical-stage therapeutic antibodies27
Assay format diversity in pre-clinical immunogenicity risk assessment: Toward a possible harmonization of antigenicity assays26
Drug-like antibodies with high affinity, diversity and developability directly from next-generation antibody libraries26
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