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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]
In the citing paper
“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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Polyreactivity increases the apparent affinity of anti-HIV antibodies by heteroligation
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Grinshpun, B., Thorsteinson, N., Pereira, J. N., Rippmann, F., Nannemann, D., Sood, V. D., & Fomekong Nanfack, Y. (2021) · mAbs · doi:10.1080/19420862.2021.1932230 · Cited by 52
“Using a set of 28 in silico properties calculated from antibody structure and 12 measurements from in vitro developability assays published by Jain et al.,22 we applied the random forest machine learning algorithm to identify biophysical properties that were best able to distinguish between normal clearing and fast cl…”
BackgroundMethodInfluentialPrediction of methionine oxidation risk in monoclonal antibodies using a machine learning method
Sankar, K., Hoi, K. H., Yin, Y., Ramachandran, P., Andersen, N., Hilderbrand, A. E., McDonald, P., Spiess, C., & Zhang, Q. (2018) · mAbs · doi:10.1080/19420862.2018.1518887 · Cited by 51
“…the desired antigen affinity and specificity, the successful therapeutic antibody development candidate needs to meet favorable developability criteria, 4 such as an optimal in vivo clearance profile, low aggregation propensity, and high levels of physical (thermal/pH) and chemical stability.”
BackgroundPharmacokinetic and Pharmacodynamic Considerations in the Design of Therapeutic Antibodies
Leipold, D. D., & Prabhu, S. (2018) · Clinical and Translational Science · doi:10.1111/cts.12597 · Cited by 56
Monoclonal antibodies: From magic bullet to precision weapon
Aboul-Ella, H., Gohar, A., Ali, A. A., Ismail, L. M., Mahmoud, A. E. E.-R., Elkhatib, W. F., & Aboul-Ella, H. (2024) · Molecular Biomedicine · doi:10.1186/s43556-024-00210-1 · Cited by 66
“Several studies [621, 622] demonstrate a relationship between the production titer and the stability of the antibody, particularly the melting temperature and solubility.”
BackgroundMason, D. M., Friedensohn, S., Weber, C. R., Jordi, C., Wagner, B., Meng, S. M., Gaínza, P., Correia, B. E., & Reddy, S. T. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/617860 · Cited by 50
“This is largely due to the fact that lead optimization of antibody molecules consists of addressing multiple parameters in parallel, including expression level, viscosity, pharmacokinetics, solubility, and immunogenicity 2,3 .”
BackgroundComparison of hydrophobicity scales for predicting biophysical properties of antibodies
Waibl, F., Fernández‐Quintero, M. L., Wedl, F. S., Kettenberger, H., Georges, G. J., & Liedl, K. R. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.960194 · Cited by 46
Accelerating therapeutic protein design with computational approaches toward the clinical stage
Chen, Z., Wang, X., Chen, X., Huang, J., Wang, C., Wang, J., & Wang, Z. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.04.027 · Cited by 49
“These factors are vital indicators for achieving success in clinical trials [8,10].”
BackgroundMakowski, E. K., Wang, T., Zupancic, J. M., Huang, J., Wu, L., Schardt, J. S., Groot, A. S. D., Elkins, S. L., Martin, W. D., & Tessier, P. M. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-023-01074-6 · Cited by 55
“%) are those with high non-specific binding and low self-association, and are exemplified by an antibody (bococizumab) that is known to display high off-target binding and immunogenicity 1,22 .”
InfluentialThe Formidable Challenge of Controlling High Mannose-Type N-Glycans in Therapeutic mAbs
Mastrangeli, R., Audino, M. C., Palinsky, W., Broly, H., & Bierau, H. (2020) · Trends in biotechnology · doi:10.1016/j.tibtech.2020.05.009 · Cited by 49
Campuzano, I. D. G., & Sandoval, W. N. (2021) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.1c00036 · Cited by 51
Jones, H. M., Zhang, Z., Jasper, P., Luo, H., Avery, L. B., King, L. E., Neubert, H., Barton, H. A., Betts, A. M., & Webster, R. (2019) · CPT Pharmacometrics & Systems Pharmacology · doi:10.1002/psp4.12461 · Cited by 48
Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity
Zhang, Y., Wu, L., Gupta, P., Desai, A. A., Smith, M. D., Rabia, L. A., Ludwig, S. D., & Tessier, P. M. (2020) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.0c00257 · Cited by 46
In vitro discovery of a human monoclonal antibody that neutralizes lethality of cobra snake venom
Ledsgaard, L., Laustsen, A. H., Puš, U., Wade, J., Villar, P., Boddum, K., Slavny, P., Masters, E. W., Arias, A. S., Oscoz, S., et al. (2022) · mAbs · doi:10.1080/19420862.2022.2085536 · Cited by 48
“Moreover, it is also known that antibody pharmacokinetics plays a significant role in drug efficacy,(32) while antibody biophysics can have a major influence on antibody manufacturability and stability.(33,34,35) Additional investigation and potential optimization of these properties and their effects on in vivo neutr…”
BackgroundWen, Y., & Jawa, V. (2020) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2020.12.003 · Cited by 51
Highly sensitive detection of antibody nonspecific interactions using flow cytometry
Makowski, E. K., Wu, L., Desai, A. A., & Tessier, P. M. (2021) · mAbs · doi:10.1080/19420862.2021.1951426 · Cited by 46
“the y-axis, while the corresponding published measurements using a proprietary yeast display technology are reported on the x-axis.(15) The PSP scores were”
BackgroundMethodResultInfluentialGupta, P., Makowski, E. K., Kumar, S., Zhang, Y., Scheer, J. M., & Tessier, P. M. (2022) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.1c00373 · Cited by 45
ALTHEA Gold Libraries™: antibody libraries for therapeutic antibody discovery
Valadon, P., Pérez‐Tapia, S. M., Nelson, R. S., Guzmán-Bringas, O. U., Arrieta-Oliva, H. I., Gómez-Castellano, K., Pohl, M. A., & Almagro, J. C. (2019) · mAbs · doi:10.1080/19420862.2019.1571879 · Cited by 47
“In parallel, as therapeutic antibody engineering and development evolved in the past decades, and dozens of antibodies were grantedmarketing approvals, it has been realized that reaching the desired specificity and affinity is not enough.(4,16) Other biological and biophysical properties such as expression, stability…”
BackgroundGentiluomo, L., Svilenov, H. L., Augustijn, D., Bialy, I. E., Greco, M. L., Kulakova, A., Indrakumar, S., Mahapatra, S., Morales, M. M., Pohl, C., et al. (2019) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.9b00852 · Cited by 46
Lai, P.-K., Fernando, A., Cloutier, T. K., Kingsbury, J. S., Gokarn, Y., Halloran, K. T., Calero-Rubio, C., & Trout, B. L. (2021) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2020.12.014 · Cited by 45
Tomar, D. S., Singh, S. K., Li, L., Broulidakis, M. P., & Kumar, S. (2018) · Pharmaceutical Research · doi:10.1007/s11095-018-2466-6 · Cited by 45
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“27,28 We also used biolayer interferometry (BLI) to measure binding kinetics and to determine avidities more accurately.”
Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods
Pérez, A.-M. W., Lorenzen, N., Vendruscolo, M., & Sormanni, P. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1450-1_4 · Cited by 43
“Therefore, biophysical properties including thermodynamic stability and solubility, but also chemical liabilities like oxidation and deamidation, play a key role in determining the success of therapeutic antibody development [8, 15, 43].”
BackgroundMethodInfluentialZero-shot antibody design in a 24-well platePreprint
Chai Discovery Team, Boitreaud, J., Dent, J., Geisz, D., McPartlon, M., Meier, J., Qiao, Z., Rogozhnikov, A., Rollins, N., Wollenhaupt, P., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.05.663018 · Cited by 56
Hebditch, M., & Warwicker, J. (2019) · PeerJ · doi:10.7717/peerj.8199 · Cited by 44
Mandal, K., Wicaksono, G., Yu, C., Adams, J., Hoopmann, M. R., Temple, W. C., Izgutdina, A., Patiño-Escobar, B., Gorelik, M., Ihling, C. H., et al. (2023) · Nature Cancer · doi:10.1038/s43018-023-00652-6 · Cited by 44
Thorsteinson, N., Gunn, J. R., Kelly, K., Long, W., & Labute, P. (2021) · mAbs · doi:10.1080/19420862.2021.1981805 · Cited by 42
Productive common light chain libraries yield diverse panels of high affinity bispecific antibodies
Blarcom, T. J. V., Lindquist, K. C., Melton, Z., Cheung‐Lee, W. L., Wagstrom, C., McDonough, D., Oseguera, C. A. V., Ding, S., Rossi, A., Potluri, S., et al. (2017) · mAbs · doi:10.1080/19420862.2017.1406570 · Cited by 42
“, a “tag control”) as well as insulin and single-stranded DNA (ssDNA) to provide a preliminary polyreactivity assessment.(42) While at least 94% of the unique antibodies from each panning bound the panned antigen, some of them also bound insulin or ssDNA resulting in 85%, 92% and 94% of all clones being assigned as an…”
BackgroundMicrofluidic Approaches for the Characterization of Therapeutic Proteins
Kopp, M. R. G., & Arosio, P. (2018) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2018.01.001 · Cited by 44
Convergent selection in antibody repertoires is revealed by deep learningPreprint
Friedensohn, S., Neumeier, D., Khan, T. A., Csepregi, L., Parola, C., de Vries, A. R. G., Erlach, L., Mason, D. M., & Reddy, S. T. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.25.965673 · Cited by 41
“…us to exhaustively sample from the naturally occurring sequence space of antibody repertoires, resulting in the in silico generation of antibody variants that retain antigen-binding, a procedure that could be used for engineering antibodies with desired therapeutic development properties 25 .”
BackgroundAlam, M. E., Barnett, G. V., Slaney, T. R., Starr, C. G., Das, T. K., & Tessier, P. M. (2019) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.8b01311 · Cited by 42
Assessing the binding properties of the anti-PD-1 antibody landscape using label-free biosensors
Brown, M. E., Bedinger, D., Lilov, A., Rathanaswami, P., Vásquez, M., Durand, S., Moyer, I. W., Zhong, L., Nett, J. H., Burnina, I., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0229206 · Cited by 42
“As in past work of this kind, we opted to create isotypematched samples, and made no attempt to reproduce the full sequences, let alone expression systems and purification processes, of the clinical molecules, in particular.[4] We should thus consider these samples as analogs of the corresponding antibody drugs or rea…”
BackgroundSelf-citationRoadmap for Drug Product Development and Manufacturing of Biologics
Sampathkumar, K., & Kerwin, B. A. (2023) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2023.11.004 · Cited by 50
Engineered Multivalent Nanobodies Potently and Broadly Neutralize SARS‐CoV‐2 Variants
Zupancic, J. M., Schardt, J. S., Desai, A. A., Makowski, E. K., Smith, M. D., Pornnoppadol, G., Barbosa, M. G. D. M., Cascalho, M., Lanigan, T. M., & Tessier, P. M. (2021) · Advanced Therapeutics · doi:10.1002/adtp.202100099 · Cited by 40
Waight, A. B., Příhoda, D., Shrestha, R., Metcalf, K. J., Bailly, M. A., Ancona, M., Widatalla, T., Rollins, Z. A., Cheng, A. C., Bitton, D. A., et al. (2023) · mAbs · doi:10.1080/19420862.2023.2248671 · Cited by 38
“1,2,49,50 We used these data in conjunction with the calculated features from the most popular software packages to implement several notable technical details, starting with the careful use of 95% sequence identity between train and testing datasets.”
MethodAn in vivo platform to select and evolve aggregation-resistant proteins
Ebo, J. S., Saunders, J. C., Devine, P. W. A., Gordon, A., Warwick, A. S., Schiffrin, B., Chin, S. E., England, E., Button, J. D., Lloyd, C., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15667-1 · Cited by 34
Svilenov, H. L., Arosio, P., Menzen, T., Tessier, P. M., & Sormanni, P. (2023) · mAbs · doi:10.1080/19420862.2022.2164459 · Cited by 40
“self-association tendency and intrinsic polyreactivity.(9,87) Interestingly, several antibodies in the study by Lecerf et al.”
BackgroundInfluentialFSH-blocking therapeutic for osteoporosis
Gera, S., Kuo, T., Gumerova, A. A., Korkmaz, F., Sant, D., DeMambro, V., Sudha, K., Padilla, A., Prévot, G., Munitz, J., et al. (2022) · eLife · doi:10.7554/elife.78022 · Cited by 40
“…algorithm based on machine learning of amino acid sequences and physicochemical variables from 136 antibodies that are FDA-approved or in late-stage clinical development (https://protein-sol.manchester.ac.uk/abpred; Hebditch and Warwicker, 2017 ; Hebditch and Warwicker, 2019 ; Jain et al., 2017 ).”
InfluentialThe Evolution of Commercial Antibody Formulations
Mieczkowski, C. (2023) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2023.03.026 · Cited by 38
Fab is the most efficient format to express functional antibodies by yeast surface display
Sivelle, C., Sierocki, R., Ferreira-Pinto, K., Simon, S., Maillère, B., & Nozach, H. (2018) · mAbs · doi:10.1080/19420862.2018.1468952 · Cited by 38
“A comprehensive study comparing the biophysical 253 properties of clinical-stage antibodies indicated that infliximab has much lower production titers in 254 HEK cells than adalimumab, certolizumab and golimumab (6 mg/L for infliximab vs more than 100 255 mg/mL for the three other anti-TNF antibodies).(41) Wittrup and…”
BackgroundSchmidt, P., Narayan, K. M., Li, Y., Kaku, C. I., Brown, M. E., Champney, E. R., Geoghegan, J. C., Vásquez, M., Krauland, E. M., Yockachonis, T. J., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.adg2783 · Cited by 35
“Finally, we confirmed that the LA modification did not significantly affect the biophysical properties of the molecule, as assessed by in vitro polyreactivity, hydrophobicity, and thermal stability assays (19) (Fig.”
BackgroundSelf-citationProtein Design and Variant Prediction Using Autoregressive Generative ModelsPreprint
Shin, J.-E., Riesselman, A. J., Kollasch, A. W., McMahon, C., Simon, E. P., Sander, C., Manglik, A., Kruse, A. C., & Marks, D. S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/757252 · Cited by 40
Lameris, R., Ruben, J. M., Iglesias‐Guimarais, V., de Jong, M., Veth, M., van de Bovenkamp, F. S., de Weerdt, I., Kater, A. P., Zweegman, S., Horbach, S., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.100961 · Cited by 40
Structural and mechanistic basis of neutralization by a pan-hantavirus protective antibody
Mittler, E., Serris, A., Esterman, E. S., Florez, C., Polanco, L. C., O’Brien, C. M., Slough, M. M., Tynell, J., Gröning, R., Sun, Y., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.adg1855 · Cited by 37
Reduction of monoclonal antibody viscosity using interpretable machine learning
Makowski, E. K., Chen, H.-T., Wang, T., Wu, L., Huang, J., Mock, M. L., Underhill, P. T., Pelegri-O’Day, E. M., Maglalang, E., Winters, D., et al. (2024) · mAbs · doi:10.1080/19420862.2024.2303781 · Cited by 37
“49,50 The physico-chemical properties of the antibodies, including Fv isoelectric point (pI), sequenced-based Fv net charge at pH 5.2, Fv charge asymmetry at pH 5.2 (the product of the V H and V L net charges), and hydrophobicity, were calculated using multiple methods.”
MethodInfluentialA dataset comprised of binding interactions for 104,972 antibodies against a SARS-CoV-2 peptide
Engelhart, E., Emerson, R., Shing, L., Lennartz, C., Guion, D., Kelley, M., Lin, C., Lopez, R. M., Younger, D. A., & Walsh, M. (2022) · Scientific Data · doi:10.1038/s41597-022-01779-4 · Cited by 37
“Outside of antibody binding, one group has published multiple manufacturability measurements for over 100 antibodies that have completed or advanced through the FDA approval pipeline 11–13 .”
BackgroundRapid directed evolution guided by protein language models and epistatic interactions
Tran, V. Q., Nemeth, M., Bartie, L. J., Chandrasekaran, S. S., Fanton, A., Moon, H. C., Hie, B., Konermann, S., & Hsu, P. D. (2026) · Science · doi:10.1126/science.aea1820 · Cited by 41
Jetha, A., Thorsteinson, N., Jmeian, Y., Jeganathan, A., Giblin, P. A., & Fransson, J. (2018) · mAbs · doi:10.1080/19420862.2018.1475871 · Cited by 36
“Generally, clinical candidates and US Food and Drug Administration-approved antibodies have relatively low HIC RT, and data for other developability experiments such as stability and aggregation fall in appropriate ranges, as described recently.(2) Computationally, when engineering antibodies, one can compare a candid…”
BackgroundMethodInfluentialAn accelerated surface-mediated stress assay of antibody instability for developability studies
Kopp, M. R. G., Pérez, A.-M. W., Zucca, M. V., Palmiero, U. C., Friedrichsen, B., Lorenzen, N., & Arosio, P. (2020) · mAbs · doi:10.1080/19420862.2020.1815995 · Cited by 33
“These results corroborate the weak link between thermal stability and other developability assays, as previously reported.(2,62)”
ResultBabi, D. K., Griesbach, J., Hunt, S., Insaidoo, F. K., Roush, D. J., Todd, R., Staby, A., Welsh, J. P., & Wittkopp, F. (2022) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2022.100813 · Cited by 36
Surface patches induce nonspecific binding and phase separation of antibodies
Ausserwӧger, H., Krainer, G., Welsh, T. J., Thorsteinson, N., de Csilléry, E., Šneideris, T., Schneider, M. M., Egebjerg, T., Invernizzi, G., Herling, T. W., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2210332120 · Cited by 35
“Despite being recognized as a vital developmental issue for the generation of therapeutic antibodies (13, 41), the physicochemical origins of nonspecificity have not been addressed sufficiently.”
BackgroundInfluentialMeta learning addresses noisy and under-labeled data in machine learning-guided antibody engineering
Minot, M., & Reddy, S. T. (2024) · Cell Systems · doi:10.1016/j.cels.2023.12.003 · Cited by 35
Characterizing various monoclonal antibodies with milder reversed phase chromatography conditions
Bobály, B., D’Atri, V., Lauber, M. A., Beck, A., Guillarme, D., & Fekete, S. (2018) · Journal of Chromatography B · doi:10.1016/j.jchromb.2018.07.039 · Cited by 35
Caffeine as a Viscosity Reducer for Highly Concentrated Monoclonal Antibody Solutions
Zeng, Y., Tran, T. H., Wuthrich, P., Naik, S., Davagnino, J., Greene, D. G., Mahoney, R. P., & Soane, D. S. (2021) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2021.06.030 · Cited by 36
Aligning protein generative models with experimental fitness via Direct Preference OptimizationPreprint
Widatalla, T., Rafailov, R., & Hie, B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.20.595026 · Cited by 35
“To this end, we evaluate on a dataset of 26 natural protein absolute stabilities ( Δ G) from Maxwell et al. [31], and thermal melting points ( 𝑇 mid ) of 483 clinical and human derived antibodies from Jain et al. and Shehata et al. [46, 21] ( Figure 3A ).”
BackgroundMethodInfluentialFerrara, F., Erasmus, M. F., D’Angelo, S., Leal‐Lopes, C., Teixeira, A. A. R., Choudhary, A. K., Honnen, W. J., Calianese, D. C., Huang, D., Peng, L., et al. (2022) · Nature Communications · doi:10.1038/s41467-021-27799-z · Cited by 36
“…of poly-speci fi city reagents 43 , af fi nity-capture self-interaction nanoparticle spectroscopy (AC-SINS) 44 , size-exclusion chromatography (SEC) after prolonged exposure to high temperature, 37 °C, and melting temperature (Tm) using differential scanning fl uorimetry (DSF) 45,46 , respectively.”
InfluentialDeciphering deamidation and isomerization in therapeutic proteins: Effect of neighboring residue
Irudayanathan, F. J., Zarzar, J., Lin, J., & Izadi, S. (2022) · mAbs · doi:10.1080/19420862.2022.2143006 · Cited by 34
Slavny, P., Hegde, M., Doerner, A., Parthiban, K., McCafferty, J., Zielonka, S., & Hoet, R. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1469329 · Cited by 33
Chaperone proteins as single component reagents to assess antibody nonspecificity
Kelly, R. L., Geoghegan, J. C., Feldman, J. E., Jain, T. S., Kauke, M. J., Le, D., Zhao, J., & Wittrup, K. D. (2017) · mAbs · doi:10.1080/19420862.2017.1356529 · Cited by 33
“All clinical stage antibodies except golimumab were expressed as human IgG1 isotype and produced as described previously.(12)”
BackgroundMethodSelf-citationPark, E., & Izadi, S. (2024) · mAbs · doi:10.1080/19420862.2024.2362788 · Cited by 32
Bashour, H., Smorodina, E., Pariset, M., Zhong, J., Akbar, R., Chernigovskaya, M., Lê Quý, K., Snapkow, I., Rawat, P., Krawczyk, K., et al. (2024) · Communications Biology · doi:10.1038/s42003-024-06561-3 · Cited by 32
“Traditionally,developabilityscreeningisperformedthroughaseriesof laborious in vitro assays 17,22,23 .”
InfluentialDevelopment of NanoLuc bridging immunoassay for detection of anti-drug antibodies
Nath, N., Flemming, R., Godat, B., & Urh, M. (2017) · Journal of Immunological Methods · doi:10.1016/j.jim.2017.07.006 · Cited by 32
“Biophysical characterization of drugs is routinely done during drug ‘developability’ studies [44, 45] and similar studies may be necessary during assay specific optimization for maximizing S/B ratio.”
BackgroundParola, C., Neumeier, D., Friedensohn, S., Csepregi, L., Tacchio, M. D., Mason, D. M., & Reddy, S. T. (2019) · mAbs · doi:10.1080/19420862.2019.1662691 · Cited by 33
“Since correct folding, stability and post-translational modifications are all important for drug development properties, the possibility to engineer antibodies in a mammalian host offers a substantial advantage in terms of developability.(7) However, the exponentially lower throughput of mammalian transfection or geno…”
BackgroundBioassay Development for Bispecific Antibodies—Challenges and Opportunities
Register, A. C., Tarighat, S. S., & Lee, H. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22105350 · Cited by 32
“Meaningful bioanalytical approaches are also needed for immunogenicity and PK/PD assessments to determine the safety and efficacy of BsAbs [78,79].”
BackgroundHobson, A. D., Xu, J., Welch, D. S., Marvin, C. C., McPherson, M. J., Gates, B. D., Liao, X., Hollmann, M., Gattner, M. J., Dzeyk, K., et al. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c01174 · Cited by 32
Atangcho, L., Navaratna, T. A., & Thurber, G. M. (2018) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2018.11.008 · Cited by 33
“process have improved pharmacokinetic properties[45].”
Conformational Ensembles of Antibodies Determine Their Hydrophobicity
Waibl, F., Fernández‐Quintero, M. L., Kamenik, A. S., Kraml, J., Hofer, F., Kettenberger, H., Georges, G. J., & Liedl, K. R. (2020) · Biophysical Journal · doi:10.1016/j.bpj.2020.11.010 · Cited by 32
“We combine state-of-the-art simulation techniques to investigate the distribution of hydrophobic regions on the surface of 126 Fv structures and compare the results with available experimental data from the literature (32).”
MethodResultDesai, A. A., Smith, M. D., Zhang, Y., Makowski, E. K., Gerson, J. E., Ionescu, E., Starr, C. G., Zupancic, J. M., Moore, S. J., Sutter, A. B., et al. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.100508 · Cited by 31
Mechanistic principles of an ultra-long bovine CDR reveal strategies for antibody design
Svilenov, H. L., Sacherl, J., Protzer, U., Zacharias, M., & Büchner, J. (2021) · Nature Communications · doi:10.1038/s41467-021-27103-z · Cited by 30
Gentiluomo, L., Roessner, D., Streicher, W. W., Mahapatra, S., Harris, P., & Frieß, W. (2019) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2019.09.021 · Cited by 31
DutaFabs are engineered therapeutic Fab fragments that can bind two targets simultaneously
Beckmann, R., Jensen, K. H., Fenn, S., Speck, J., Krause, K., Meier, A., Röth, M., Fauser, S., Kimbung, Y. R., Logan, D. T., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-20949-3 · Cited by 30
Agonist antibody discovery: Experimental, computational, and rational engineering approaches
Schardt, J. S., Jhajj, H. S., O’Meara, R. L., Lwo, T. S., Smith, M. D., & Tessier, P. M. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2021.09.008 · Cited by 32
Nature-inspired design and evolution of anti-amyloid antibodies
Julian, M. C., Rabia, L. A., Desai, A. A., Arsiwala, A., Gerson, J. E., Paulson, H. L., Kane, R. S., & Tessier, P. M. (2019) · Journal of Biological Chemistry · doi:10.1074/jbc.ra118.004731 · Cited by 30
“We used an ELISA method (39,40) that measures antibody nonspecific binding to six different types of immobilized molecules with diverse chemical properties (cardiolipin, keyhole limpet”
MethodLooking for therapeutic antibodies in next generation sequencing repositories
Krawczyk, K., Raybould, M., Kovaltsuk, A., & Deane, C. M. (2019) · doi:10.1101/572958 · Cited by 29
“reflect the myriad antibody types, including fully human, humanized, chimeric or fully mouse.(19) The individual identities of the CSTs with respect to the best match from OAS are”
BackgroundSelective Tryptophan Oxidation of Monoclonal Antibodies: Oxidative Stress and Modeling Prediction
Pavon, J. A., Xiao, L., Li, X., Zhao, J., Aldredge, D. L., Dank, E., Fridman, A., & Liu, Y. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04768 · Cited by 29
Kaleli, N. E., Karadag, M., & Kalyoncu, S. (2019) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25685 · Cited by 29
Cross-Reactivity and Functionality of Approved Human Immune Checkpoint Blockers in Dogs
Pantelyushin, S., Ranninger, E., Guerrera, D., Hütter, G., Maake, C., Markkanen, E., Bettschart‐Wolfensberger, R., Bley, C. R., Laubli, H. P., & Berg, J. V. (2021) · Cancers · doi:10.3390/cancers13040785 · Cited by 29
“Additionally, well-characterized approved human antibodies generally have superior biophysical properties and ‘developability’, which significantly improves their success as a potent therapeutic [19,20].”
Page, S., Khan, T. A., Kühl, P. G., Schwach, G., Storch, K., & Chokshi, H. P. (2022) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-052120-093517 · Cited by 28
Hicks, D. M., Baehr, C., Silva-Ortiz, P., Khaimraj, A., Luengas, D., Hamid, F. A. A. A., & Pravetoni, M. (2022) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2022.2122507 · Cited by 31
Mock, M. L., Jacobitz, A. W., LANGMEAD, C. J., Sudom, A. M., Yoo, D., Humphreys, S. C., Alday, M., Alekseychyk, L., Angell, N., Bi, V., et al. (2023) · mAbs · doi:10.1080/19420862.2023.2256745 · Cited by 29
“…isomerization values are lower than those reported by Lu et al. 44 Our HIC retention times are also more extended than those reported by Jain et al. 15 Both attribute differences reflect differences in the protein sequence distribution as well as in methods and conditions, and such differences may…”
BackgroundResultInfluentialEngineering of anti-human interleukin-4 receptor alpha antibodies with potent antagonistic activity
Kim, J.-E., Jung, K., Kim, J.-A., Kim, S., Park, H., & Kim, Y. (2019) · Scientific Reports · doi:10.1038/s41598-019-44253-9 · Cited by 32
The evolution of bispecific antibodies
Gera, N. (2022) · Expert Opinion on Biological Therapy · doi:10.1080/14712598.2022.2040987 · Cited by 33
Multiscale pharmacokinetic modeling of systemic exposure of subcutaneously injected biotherapeutics
Zheng, F., Hou, P., Corpstein, C. D., Park, K., & Li, T. (2021) · Journal of Controlled Release · doi:10.1016/j.jconrel.2021.07.043 · Cited by 28
Large-scale application of free energy perturbation calculations for antibody design
Zhu, F., Bourguet, F. A., Bennett, W. F., Lau, E. Y., Arrildt, K. T., Segelke, B. W., Zemla, A. T., Desautels, T., & Faissol, D. (2022) · Scientific Reports · doi:10.1038/s41598-022-14443-z · Cited by 28
“(13) can be approximated as G0→a,b ≈ G0→a + G0→b .”
Kumar, S., Roffi, K., Tomar, D. S., Cirelli, D. J., Luksha, N., Meyer, D., Mitchell, J., Allen, M. J., & Li, L. (2018) · Protein Engineering Design and Selection · doi:10.1093/protein/gzy020 · Cited by 28
“Computational analyses have been shown to yield novel insights into properties of the biologic drug candidates when combined with high quality data collected from experiments performed under standardized conditions (Li et al., 2014; Sharma et al., 2014; Jain et al., 2017; Tomar et al., 2017).”
BackgroundMorales, I. C., Dingfelder, F., Waibel, I., Turnbull, O. M., Patel, B., Cao, Z., Bjelke, J. R., Grell, S. N., Bennet, A., Hummer, A. M., et al. (2024) · mAbs · doi:10.1080/19420862.2024.2403156 · Cited by 27
“As observed in other studies, 17,34,35 poor correlations were observed, and no individual property could predict the long-term stability of the variants (Suppl.”
BackgroundResultInfluentialHeads, J. T., Lamb, R., Kelm, S., Adams, R., Elliott, P., Tyson, K. L., Topia, S., West, S. M., Nan, R., Turner, A. V., et al. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzz046 · Cited by 30
“An undesirable side effect of variable region sequence diversity is the broad range of aggregation propensities observed for mAbs (Jain et al., 2017).”
BackgroundEngineering soluble T‐cell receptors for therapy
Robinson, R. A., McMurran, C., McCully, M. L., & Cole, D. K. (2021) · FEBS Journal · doi:10.1111/febs.15780 · Cited by 29
Hobson, A. D., Xu, J., Marvin, C. C., McPherson, M. J., Hollmann, M., Gattner, M. J., Dzeyk, K., Fettis, M. M., Bischoff, A. K., Wang, L., et al. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c00794 · Cited by 27
Determination of Protein–Protein Interactions in a Mixture of Two Monoclonal Antibodies
Singh, P. A., Roche, A., van der Walle, C. F., Uddin, S., Du, J., Warwicker, J., Pluen, A., & Curtis, R. (2019) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.9b00430 · Cited by 27
Recent Progress in Capturing and Neutralizing Inflammatory Cytokines
Zhang, Q., Gong, H., Gao, W., & Zhang, L. (2020) · CCS Chemistry · doi:10.31635/ccschem.020.202000165 · Cited by 27
Harnessing SLE Autoantibodies for Intracellular Delivery of Biologic Therapeutics
Gordon, R. E., Nemeth, J. F., Singh, S., Lingham, R. B., & Grewal, I. S. (2020) · Trends in biotechnology · doi:10.1016/j.tibtech.2020.07.003 · Cited by 26
Makowski, E. K., Chen, H., Lambert, M. A., Bennett, E. M., Eschmann, N. S., Zhang, Y., Zupancic, J. M., Desai, A. A., Smith, M. D., Lou, W., et al. (2022) · mAbs · doi:10.1080/19420862.2022.2146629 · Cited by 25
“27,33 Interestingly, our immunoconjugates facilitated the isolation of antibodies with broad improvements to their biophysical properties beyond simply reducing their self-association in PBS (pH 7.4).”
BackgroundMethodInfluentialThe therapeutic antibody profiler for computational developability assessment
Raybould, M. I. J., & Deane, C. M. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-1450-1_5 · Cited by 25
Data mining patented antibody sequences
Krawczyk, K., Buchanan, A. G., & Marcatili, P. (2021) · mAbs · doi:10.1080/19420862.2021.1892366 · Cited by 25
“Many features of therapeutic antibodies can be found in naturally sourced sequences,(5) but effective biotherapeutic requires bespoke engineering for clinical safety and developability.(2) We proposed that such biotherapeutic engineering knowledge could be reflected in patent documents containing antibody sequences.”
BackgroundHersey, S., Keller, S., Mathews, J. A., King, L., Bandukwala, A., Berisha, F., Birchler, M., Bower, J., Clausen, V. A., Duarte, J., et al. (2022) · Bioanalysis · doi:10.4155/bio-2022-0080 · Cited by 25
Self-citationHow can we discover developable antibody-based biotherapeutics?
Bauer, J., Rajagopal, N., Gupta, P., Gupta, P. K., Nixon, A. E., & Kumar, S. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1221626 · Cited by 28
Arras, P., Yoo, H. B., Pekar, L., Clarke, T., Friedrich, L., Schröter, C. J., Schanz, J., Tonillo, J., Siegmund, V., Doerner, A., et al. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1249247 · Cited by 25
“The calculated scores indicate favorable colloidal stability properties for all tested SEEDbodies, very similar to trastuzumab and significantly better compared to briakinumab, which was used as reference with a known propensity for self-interaction (Jain et al., 2017).”
BackgroundData-driven engineering of protein therapeutics
Faber, M. S., & Whitehead, T. A. (2019) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2019.01.015 · Cited by 26
i-shaped antibody engineering enables conformational tuning of biotherapeutic receptor agonists
Romei, M. G., Leonard, B. C., Katz, Z., Le, D., Yang, Y., Day, E. S., Koo, C. W., Sharma, P. A., Bevers, J. J., Kim, I., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44985-x · Cited by 24
Nannini, F., Senicar, L., Parekh, F., Kong, K. J., Kinna, A., Bughda, R., Sillibourne, J., Hu, X. S., Ma, B., Bai, Y., et al. (2020) · mAbs · doi:10.1080/19420862.2020.1864084 · Cited by 24
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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