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Biophysical properties of the clinical-stage antibody landscape
Open accessAbstract
Significance: In addition to binding to a desired target molecule, all antibody drugs must also meet a set of criteria regarding the feasibility of their manufacture, stability in storage, and absence of off-target stickiness. This suite of characteristics is often termed “developability.” We present here a comprehensive analysis of these properties for essentially the full set of antibody drugs that have been tested in phase-2 or -3 clinical trials, or are approved by the FDA. Surprisingly, many of the drugs or candidates in this set exhibit properties that indicate significant developability risks; however, the number of such red warning flags decreases with advancement toward approval. This reference dataset should help prioritize future drug candidates for development.
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“The increasing number of structural [16], sequence [17] and experimental data [18–21] on antibodies being deposited in the public domain provides the necessary foundation for improving such data-driven methods.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [21]
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“and Jain et al. demonstrated the feasibility of using multiple biophysical metrics to characterize mAbs for drug‐like behavior.58”
From Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development (2018) · cites this paper as [58]
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“whether obtained from internally manufactured and developed molecules or through external benchmarks of publicly available antibody therapeutics.(2) Indeed, a more comprehensive assessment of candidates from different perspectives is critical to the lead candidate decision-making process.”
BackgroundProtein Stability After Administration: A Physiologic Consideration
Schuster, J., Kamuju, V., & Mathaes, R. (2022) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2022.09.032 · Cited by 6
Predictive Nature of High-Throughput Assays in ADC Formulation Screening
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Germinality does not necessarily define mAb expression and thermal stability
Schwaigerlehner, L., Mayrhofer, P., Diem, M., Steinfellner, W., Fenech, E. J., Oostenbrink, C., & Kunert, R. (2019) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-019-09998-3 · Cited by 6
Membrane Proteins as Targets for Biological Drugs
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“Susceptibility to non-specific binding can be further tested via baculovirus (BVP) ELISA [1].”
InfluentialAn antibody developability triaging pipeline exploiting protein language models
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“26,27 However, it has become useful to predict these features at an earlier stage using computational means.”
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“Upon manual inspection, this structure has a very long,compactCDR3loop,whichcanincreasethelikelihoodofitcontaining larger,morehydrophobicresiduestointeractwiththeFR2region 46 andmay potentially lead to increased non-speci fi c binding, which is captured by the BVP-ELISA 61 .”
InfluentialEngineering a pure and stable heterodimeric IgA for the development of multispecific therapeutics
Heinkel, F., Verstraete, M. M., Cao, S., Li, J., Farber, P. J., Stangle, E., Silva‐Moreno, B., Peng, F., Dixit, S. B., Boulanger, M. J., et al. (2022) · mAbs · doi:10.1080/19420862.2022.2141637 · Cited by 5
Stability convergence in natural antibodies with ultra-long hypervariable loops
Passon, M., Zalar, M., Nehls, T., Smedt, S. C. D., Lermyte, F., Mehdipour, A. R., & Svilenov, H. L. (2025) · Communications Biology · doi:10.1038/s42003-025-08036-5 · Cited by 5
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Matrixed CDR grafting: A neoclassical framework for antibody humanization and developability
Gupta, P., Horspool, A. M., Trivedi, G., Moretti, G., Datar, A., Huang, Z.-F., Chiecko, J., Kenny, C. H., & Marlow, M. S. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.105555 · Cited by 6
Harrison, M. C., & Lai, P. (2024) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.4c00879 · Cited by 5
A role for macromolecular crowding in off-target binding of therapeutic antibodies
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An effective strategy for the humanization of antibody fragments under an accelerated timeline
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“Increasingly, favorable antibody developability characteristics are considered essential for therapeutic development and have been correlated with progression to late-stage development [14].”
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Drug-like antibody design against challenging targets with atomic precisionPreprint
Chai Discovery Team, Boitreaud, J., Chen, R. S., Dent, J., Fairweather, L., Geisz, D., Greenig, M., Boyd, N., Jain, J., Johnston, B., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.29.691346 · Cited by 9
“If a peak was unresolvable we reported the retention time as an arbitrary 25 minutes [8].”
InfluentialTrenker, R., Rokkam, D., Morin, A., Balasubrahmanyam, P., Paredes, V., Cheng, I., Malefyt, R. D. W., Oft, M., Lupardus, P. J., & Vivona, S. (2025) · Antibodies · doi:10.3390/antib14030074 · Cited by 4
“However, the importance of thermal stability in the drug-like properties of a candidate biologic [26,27] may make this strategy an important engineering tool for future VHH-based multispecific development.”
Abeer, A. N. M. N., Boroumand, M., Sermadiras, I., Caldwell, J. G., Stanev, V., Mody, N., Kaplan, G., Savery, J., Croasdale-Wood, R., & Pouryahya, M. (2025) · mAbs · doi:10.1080/19420862.2025.2562997 · Cited by 4
Incorporating mRNA therapeutics into biological treatments of hematologic malignancies
Hunia, J., Tomasik, J., Czerwik, N., Pezeshki, P. S., & Nowis, D. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1680071 · Cited by 6
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“Develop-ability was evaluated using polyspecific reactivity (PSR) and hydrophobicity interacting column (HIC) binding profiles [39, 42].”
Off-target reactivity in clinical monoclonal antibodies
Dai, Y., Brouillard, J., Jaycox, J. R., Yeon, S. M., Huck, J. D., Yandamuri, S. S., Zhong, Z., O'Connor, K. C., Burnina, I., Henkel, C., et al. (2026) · Structure · doi:10.1016/j.str.2026.02.012 · Cited by 4
Application of protein language models for antibody developability prediction
Amini, S., Huang, Y., Julian, M. C., Palmer, C., Sciabola, S., & Wang, Y. C. (2026) · mAbs · doi:10.1080/19420862.2026.2647489 · Cited by 4
“…sets of clinical-stage antibodies, all PSR, HIC, and AC-SINS measurements were generated using protocols consistent with those described by Jain et al. (2017): PSR and AC-SINS were measured in PBS-based buffers at pH 7.4, while HIC was run at pH 6.8 using a 20 min ammonium sulfate…”
InfluentialMetcalf, K. J., Wo, G., Zaragoza, J. P. T., Raoufi, F., Baker, J., Chen, D., Derebe, M. G., Hogan, J. M., Hsu, A. H.-M., Kofman, E., et al. (2025) · mAbs · doi:10.1080/19420862.2025.2502127 · Cited by 4
“The NSB Average ELISA assay followed the methods of Jain et al. 8 Briefly, ELISA assays were run with six different antigens: cardiolipin (50 μg/mL, Sigma #C0563), dsDNA (1 μg/ mL, Sigma #D4522), ssDNA (1 μg/mL, Sigma #D8899), insulin (5 μg/mL, Sigma #I9278), KLH (5 μg/mL, Sigma #H8283), and LPS…”
InfluentialXu, J., Namanja, A. T., Chan, S. L., Son, C., Petros, A. M., Sun, C. C., Radziejewski, C. H., & Ihnat, P. M. (2021) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2021.09.005 · Cited by 4
Analytical Workflows to Unlock Predictive Power in Biotherapeutic Developability
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“[9] observed redundancy in the data output from 12 developability assays which suggests that a degree of overlap exists in the information being gathered by the reported parameters across different assays.”
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Sawmynaden, K., Wong, N. C. L., Davies, S. L., Cowan, R. H., Brown, R., Tang, D. G., Henry, M., Tickle, D. C., Matthews, D. J., Carr, M. D., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0288259 · Cited by 4
“Biophysical characterisation of early-stage biologics is important to identify any associated risks or safety concerns, prior to beginning ‘good manufacturing practice’ (GMP) scale production and subsequently clinical trials [35].”
BackgroundHumanization of Pan-HLA-DR mAb 44H10 Hinges on Critical Residues in the Antibody Framework
Kassardjian, A., Ivanochko, D., Barber, B. H., Jetha, A., & Julien, J. (2024) · Antibodies · doi:10.3390/antib13030057 · Cited by 5
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BackgroundFacile generation of drug-like conformational antibodies specific for amyloid fibrils
Desai, A. A., Zupancic, J. M., Trzeciakiewicz, H., Gerson, J. E., Dubois, K. N., Skinner, M. E., Sharkey, L. M., McArthur, N., Ferris, S. P., Bhatt, N. N., et al. (2025) · Nature Chemical Biology · doi:10.1038/s41589-025-01881-9 · Cited by 4
“https://doi.org/10.1038/s41589-025-01881-9 antibodies generated using immunization are well known to commonly possess superior properties relative to those developed using nonimmune or synthetic libraries 12,13 .”
InfluentialTherapeutic antibody discovery
Hoover, J. M., Prinslow, E. G., Teigler, J. E., Truppo, M. D., & LaPorte, S. L. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-820007-0.00023-4 · Cited by 4
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“The biophysical properties of a therapeutic antibody can critically influence its late-stage developability, which requires high-level expression, high solubility, conformational and colloidal stability, low polyspecificity, and low immunogenicity [33].”
BackgroundDietlin-Auril, V., Lecerf, M., Depinay, S., Noé, R., & Dimitrov, J. D. (2021) · Molecular Immunology · doi:10.1016/j.molimm.2021.10.019 · Cited by 4
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AAPS Perspective on the EURL Recommendation on the use of Non-Animal-Derived Antibodies
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Surface interaction patches link non-specific binding and phase separation of antibodiesPreprint
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Flow cytometric isolation of drug-like conformational antibodies specific for amyloid fibrilsPreprint
Desai, A. A., Zupancic, J. M., Trzeciakiewicz, H., Gerson, J. E., Dubois, K. N., Skinner, M. E., Sharkey, L. M., McArthur, N., Ferris, S. P., Bhatt, N. N., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.04.547698 · Cited by 4
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Precise, Specific, and Sensitive De Novo Antibody Design Across Multiple CasesPreprint
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“The reaction was stopped by adding stop solution, and the absorbance was measured at OD 450 [17].”
Origin-1: a generative AI platform for de novo antibody design against novel epitopesPreprint
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Biophysical Analysis of Therapeutic Antibodies in the Early Development Pipeline
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Zhou, Y., Tang, H., Wu, C., Zhang, Z., Wei, J., Gong, R., Gunarathne, S. M. S., Xiang, C., & Huang, J. H. (2025) · Journal of Pharmaceutical Analysis · doi:10.1016/j.jpha.2025.101448 · Cited by 3
“The PSR SMP score of 131 mAbs were obtained from Jain et al. [32].”
InfluentialVelappan, N., Biryukov, S. S., Rill, N. O., Klimko, C. P., Rosario-Acevedo, R., Shoe, J. L., Hunter, M., Dankmeyer, J. L., Fetterer, D. P., Bedinger, D., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0305034 · Cited by 3
Engineered SH3-Derived Sherpabodies Function as a Modular Platform for Targeted T-cell Immunotherapy
Hernández-López, R. A., Kesti, T., Mäkelä, A. R., Zhao, Z., Yu, W., Tonai, Y., Monzó, H. J., Kalander, K., Leppä, S., Ojala, P. M., et al. (2025) · Cancer Research · doi:10.1158/0008-5472.can-24-1959 · Cited by 3
“Furthermore, a “sticky macromolecule” ELISA, designed to detect nonspecific interactions by including compounds known for promiscuous binding (19, 20), demonstrated that the selected sherpabodies did not exhibit poly-reactive nonspecific binding (Supplementary Fig.”
Okada, R., Shibata, K., Shibuya, R., Torisu, T., & Uchiyama, S. (2025) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2025.107060 · Cited by 3
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“…fewer molecular liability risks have greater overall physicochemical stability leading to higher probability of success of completing clinical trials and becoming commercial products, 9 hence new methods to predict stability or validate intrinsic molecular risks would be of significant benefit.”
Pragmatic mAb lead molecule engineering from a developability perspective
Chi, B., Oliveira, G. D., Gallagher, T., Mitchell, L., Knightley, L., Gonzalez, C. C., Russell, S., Germaschewski, V., Pearce, C., & Sellick, C. A. (2021) · Biotechnology and Bioengineering · doi:10.1002/bit.27802 · Cited by 3
“It has become increasingly recognized in the biologics R&D field the importance of lead molecule developability alongside functionality (Heads et al., 2019; Jain et al., 2017; Wolf Pérez et al., 2019; Rabia et al., 2018; Raybould et al., 2019; Wijesuriya et al., 2018).”
BackgroundMethodZhong, X., Schenk, J., Sakorafas, P., Chamberland, J. P., Tam, A. S. P., Thomas, L. M., Yan, G., D’Antona, A. M., Lin, L., Nocula‐Ługowska, M., et al. (2022) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2022.10.016 · Cited by 3
Multi-state modeling of antibody-antigen complexes with SAXS profiles and deep-learning models
Cohen, T., Halfon, M., Carter, L. G., Sharkey, B., Jain, T. S., Sivasubramanian, A., & Schneidman‐Duhovny, D. (2022) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2022.11.003 · Cited by 3
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Engineering Antibodies and Alternative Binders for Therapeutic Uses
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Transgenic Animals for the Generation of Human Antibodies
Ma, B., & Osborn, M. J. (2020) · Learning materials in biosciences · doi:10.1007/978-3-030-54630-4_5 · Cited by 5
LegoBody: facile generation of bispecific and multi-specific antibodiesPreprint
Lang, S., Yang, S., Bidlingmaier, S. M., Lee, N.-K., & Liu, B. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.25.888586 · Cited by 3
Divining Deamidation and Isomerization in Therapeutic Proteins: Effect of Neighboring ResiduePreprint
Irudayanathan, F. J., Zarzar, J., Lin, J., & Izadi, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.26.453885 · Cited by 3
“Protein stability is at the center of biological mechanisms spanning molecular pathways and therapeutic interventions.[1-3] Proteins are subject to various post-translational modifications (PTM) that are essential”
BackgroundEngineering Antibody‐Based Therapeutics: Progress and Opportunities
Nguyen, A. W., & Maynard, J. A. (2021) · Wiley eBooks · doi:10.1002/9783527815128.ch13 · Cited by 4
PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity and Antibody DevelopabilityPreprint
Waibl, F., Pomarici, N. D., Hoerschinger, V. J., Loeffler, J. R., Deane, C. M., Georges, G. J., Kettenberger, H., Fernández‐Quintero, M. L., & Liedl, K. R. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.14.547811 · Cited by 3
Molecular Surface Descriptors to Predict Antibody DevelopabilityPreprint
Park, E., & Izadi, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.18.549448 · Cited by 3
Antibody immunogenicity prediction and optimization with ImmunoSeqPreprint
Huang, Q., He, Y., & Liu, K. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.14.670305 · Cited by 3
High-Throughput Protein Expression Screening of Cell-Surface Protein Ectodomains
Ghosh, A., Yang, C., Lloyd, K., & Meijers, R. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-3878-1_19 · Cited by 2
Rationalizing mAb Candidate Screening Using a Single Holistic Developability Parameter
Willis, L. F., Trayton, I., Saunders, J. C., Brùque, M. G., Birch, W. D., Westhead, D. R., Day, K., Bond, N. J., Devine, P. W. A., Lloyd, C., et al. (2024) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.4c00829 · Cited by 2
Localization of G3A1b Destroyed by Heat Treatment and Identification of Allergenic Amino Acids
Duan, Y., Gao, Y., Yang, H., Shui, T., Huang, P., Qu, J., He, R., & Xi, J. (2025) · Journal of Agricultural and Food Chemistry · doi:10.1021/acs.jafc.4c11125 · Cited by 2
Prediction of antibody non-specificity using protein language models and biophysical parameters
Sakhnini, L. I., Beltrame, L., Fulle, S., Sormanni, P., Henriksen, A., Lorenzen, N., Vendruscolo, M., & Granata, D. (2026) · mAbs · doi:10.1080/19420862.2026.2678000 · Cited by 3
“12,25 Initially, these biomolecules were studied as model antigens for autoimmune responses and diseases.”
InfluentialAutomation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations
Radford, D. C., Tamasi, M., Mare, E. D., & Gormley, A. J. (2026) · Advanced Science · doi:10.1002/advs.76551 · Cited by 2
“Furthermore, differences in physiochemical properties between individual antibodies limits the ability to extrapolate formulation performance from one to another [ 21–23 ].”
AB‐Panda: An AI‐Generated Antibody Structure‐Based Tool for Developability Prediction
Zou, W., Deng, J., Shen, Y., Zhang, T., Bing, Z., Yuan, L., Huang, C., Liu, J., & Li, X. L. (2025) · Biotechnology and Bioengineering · doi:10.1002/bit.70086 · Cited by 2
“Since higher values in these assays indicate greater hydrophobicity, the top two antibodies, lirilumab and glembatumumab, were chosen for AB ‐ Panda's evaluation (Supporting Information Table S2).”
InfluentialMeng, Y., Wang, L., Yang, Y., Su, L., Ge, Y., Xi, H., Lin, S., Chen, Y., Liu, W., Wang, W., et al. (2025) · mAbs · doi:10.1080/19420862.2025.2597610 · Cited by 2
“10 We note that developability is influenced by additional factors beyond native chain pairing, including aggregation propensity, expression level, and other biophysical properties, 11 which are considered in downstream optimization.”
Forder, J. K., Şahin, E., & Roberts, C. J. (2025) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.5c01398 · Cited by 2
A pharmaceutical developability perspective on antibodies with ultra-long CDRs
Passon, M., Smedt, S. C. D., & Svilenov, H. L. (2025) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2025.104142 · Cited by 2
Nonspecific Cellular Interactions Are a Key Determinant in the Disposition of Fc-Fused Proteins
Bryniarski, M. A., Wang, S., Chen, A., Coventry, B., Korkmaz, E. N., Tuhin, M. T. H., Ko, E. C., Wakefield, D. L., LaGory, E. L., Wu, H., et al. (2026) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.5c01228 · Cited by 4
Arsiccio, A., Mutschler, H., Pedro, A. S., Pabstmann, T., Helbig, C., Brandstetter, D., Cerasoli, E., Hawe, A., & Menzen, T. (2026) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2026.104196 · Cited by 2
Tomasoni, D., Paris, A., Visintainer, R., Cook, K. D., Chen, A., Figueroa, I., Thomas, V. A., & Marchetti, L. (2026) · The AAPS Journal · doi:10.1208/s12248-026-01232-z · Cited by 2
“Previous works have identified potential factors affecting the non-specific binding of mAbs or mAb-derived therapeutics, such as isoelectric point (7), charged patches (8, 9), and hydrophobicity (10).”
DualGPT-AB: a dual-stage generative optimization framework for therapeutic antibody design
Xie, D., Chen, S., Zeng, X., Lu, D., Jiao, S., Xiao, S., Liu, J., Hao, J., Dai, H., & Peng, J. (2026) · Nature Computational Science · doi:10.1038/s43588-026-00976-0 · Cited by 2
“Under comparable conditions, DualGPT-AB achieved a higher overall success rate (Supplementary Note 1 and Supplementary Table 1).”
InfluentialAlmagro, J. C., Gómez-Castellano, K., Licona‐Limón, I., Carballo‐Uicab, G., Ramírez-Villedas, F., Montes-Luna, A., González‐González, E., Godínez-Palma, S., Barrera-Saldaña, H. A., & Pérez‐Tapia, S. M. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1834585 · Cited by 2
Thorsteinson, N., Comeau, S. R., & Kumar, S. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2609-2_11 · Cited by 2
Datta‐Mannan, A., Molitoris, B. A., Feng, Y., Irizarry, M. M. M., Sandoval, R. M., Brown, R. M., Merkel, D., Croy, J. E., & Dunn, K. W. (2022) · Drug Metabolism and Disposition · doi:10.1124/dmd.122.001049 · Cited by 2
“…hydrophobic interactions, have been empirically connected to PK behavior (Boswell et al., 2010; Igawa et al., 2010; Datta-Mannan et al., 2015, 2020; Jain et al., 2017; Hu and D'Argenio 2020; Grinshpun et al., 2021); thus, it seems reasonable to speculate that the increased propensity of G 4…”
BackgroundMinimal purification method enables developability assessment of recombinant proteins
Rodriguez‐Aponte, S. A., Naranjo, C. A., Johnston, R. S., Dalvie, N. C., Crowell, L. E., Bajoria, S., Kumru, O. S., Joshi, S. B., Volkin, D. B., & Love, J. C. (2023) · Biotechnology and Bioengineering · doi:10.1002/bit.28385 · Cited by 2
“An evaluation of the clinical stage and approved antibodies revealed that approved candidates included significantly less devel-opability risks, suggesting a correlation with their approval rate (Jain et al., 2017).”
Pang, G., Wang, R., Yang, H., Chai, M., Gao, Y., Chen, S., Mao, T., Du, L., Lan, Y., Li, S., et al. (2025) · Protein Science · doi:10.1002/pro.70090 · Cited by 2
Modifying recombinant purple acid phosphatase using computational design
Venkatramani, A., Ali, M., Predeina, O., Molloy, J., Sormanni, P., & Hall, E. A. H. (2025) · European Biophysics Journal · doi:10.1007/s00249-025-01779-3 · Cited by 2
“Proteins frequently exhibit a delicate balance between stability, solubility, and biological function, where modifications improving one characteristic can inadvertently compromise another (Jain et al. 2017).”
Engineering Antibodies as Drugs: Principles and Practice
Lugovskoy, A. A. (2017) · Molecular Biology · doi:10.1134/s0026893317060097 · Cited by 2
Hybrid Mass Spectrometry Applied across the Production of Antibody Biotherapeutics
Christofi, E., O’Hanlon, M., Curtis, R., Barman, A., Keen, J. N., Nagy, T., & Barran, P. E. (2024) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.4c00253 · Cited by 2
Engineering an EGFR‐binding Gp2 domain for increased hydrophilicity
Du, F., Kruziki, M. A., Zudock, E. J., Zhang, Y., Lown, P. S., & Hackel, B. J. (2018) · Biotechnology and Bioengineering · doi:10.1002/bit.26893 · Cited by 2
“Beyond size and domain architecture, other physical and chemical characteristics, such as hydrophilicity, solubility and stability, are significant for protein utility and developability (Jacobs, Wu, Feng, Bethea, & O’Neil, 2010; Jain et al., 2017).”
BackgroundAn in silico method to assess antibody fragment polyreactivityPreprint
Harvey, E. P., Shin, J.-E., Skiba, M. A., Nemeth, G. R., Hurley, J. D., Wellner, A., Shaw, A. Y., Miranda, V. G., Min, J., Liu, C. C., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.12.476085 · Cited by 2
Sequence-Based Prediction of Ph-Dependent Protein Solubility Using CamsolPreprint
Oeller, M., Kang, R. J. D., Bell, R., Ausserwӧger, H., Sormanni, P., & Vendruscolo, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4189397 · Cited by 2
Mandal, K., Wicaksono, G., Yu, C., Adams, J., Hoopmann, M. R., Temple, W. C., Patiño-Escobar, B., Gorelik, M., Ihling, C. H., Nix, M. A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.10.511511 · Cited by 2
SUMO – In Silico Sequence Assessment Using Multiple Optimization ParametersPreprint
Evers, A., Malhotra, S., Bolick, W.-G., Najafian, A., Borisovska, M., Warszawski, S., Fomekong‐Nanfack, Y., Kühn, D., Rippmann, F., Crespo, A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.19.517175 · Cited by 2
Case, M., Smith, M., Vinh, J., & Thurber, G. M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.09.544229 · Cited by 2
“58 We observed that the set of sequences predicted to be co-optimal by ILP are similar to their most optimal clones identified experimentally.”
BackgroundAusterberry, J. I., Edwards, J., Eyes, T. J., & Derrick, J. P. (2021) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.1c00543 · Cited by 1
Bioelectrochemical Treatment of Petrochemicals
Kumar, N., Tavker, N., Kumar, P., & Singh, S. (2023) · Environmental science and engineering · doi:10.1007/978-3-031-46858-2_10 · Cited by 1
Cook, K. D., Tran, T. B., Thomas, V. A., Devanaboyina, S. C., Rock, D. A., & Pearson, J. T. (2023) · Drug Metabolism and Disposition · doi:10.1124/dmd.123.001555 · Cited by 1
“…binding and non-specific binding, have been rigorously tested for their ability to successfully characterize potential in vivo pharmacokinetic liabilities in monoclonal antibodies (mAbs) (Avery et al., 2018; Datta-Mannan et al., 2015; Grinshpun et al., 2021; Jain et al., 2017; Kelly et al., 2016).”
BackgroundHuang, R. R., Spliedt, M., Kaufman, T., Gorlatov, S. N., Barat, B., Shah, K., Gill, J., Stahl, K., DiChiara, J., Wang, Q., et al. (2025) · Antibodies · doi:10.3390/antib14010007 · Cited by 1
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Szkodny, A. C., & Lee, K. H. (2025) · Biotechnology Journal · doi:10.1002/biot.70102 · Cited by 1
“The trendwasrecentlyextendedtomammaliansystems,mostnotably in a recent developability assessment that found a correlation between mAb melting temperature and transient expression titers in HEK293 [5].”
Metadata
- Authors
- Jain, T., Sun, T., Durand, S., Hall, A., Houston, N. R., Nett, J. H., Sharkey, B., Bobrowicz, B., Caffry, I., Yu, Y., Cao, Y., Lynaugh, H., Brown, M., Baruah, H., Gray, L. T., Krauland, E. M., Xu, Y., Vásquez, M., & Wittrup, K. D.
- Affiliations
- Adimab (United States) (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2017-01-17
- Volume
- 114
- Issue
- 5
- Pages
- 944-949
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC5293111
- OpenAlex
- W2578029714
- Cited by
- 629
- References
- 33
- Citations by year
- 2026: 84 · 2025: 75 · 2024: 75 · 2023: 83 · 2022: 80 · 2021: 71 · 2020: 52 · 2019: 58 · 2018: 35 · 2017: 15
- FWCI
- 33.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
- Life Sciences › Immunology and Microbiology › Immunology › Biosimilars and Bioanalytical Methods
- Keywords
- therapeutic antibodies, antibody developability, biophysical properties, IgG1 antibodies, antibody engineering, drug-likeness
- MeSH terms
- Amino Acid Sequence, Antibodies, Monoclonal, Humans, Immunoglobulin G, Drug Approval, Biophysical Phenomena, Drug Discovery, HEK293 Cells
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