{"entity": "researcher", "timestamp": "2026-08-20T21:50:17.280Z", "family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "affiliations": ["Prosilico AB, Huddinge, Sweden."], "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b"}}, "publications": [{"entity": "publication", "iuid": "e5a582ced3d64984a863733e97932ac6", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e5a582ced3d64984a863733e97932ac6.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e5a582ced3d64984a863733e97932ac6"}}, "title": "Comparing Lipinskis Rule of 5 and Machine Learning Based Prediction of Fraction Absorbed for Assessing Oral Absorption in Humans", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Ekmefjord", "given": "Morgan", "initials": "M"}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2024-08-23", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2024.08.20.608791", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:58:17.628Z", "modified": "2026-08-20T10:58:17.655Z"}, {"entity": "publication", "iuid": "438a9eb2590543ad9cd61d22f2825931", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/438a9eb2590543ad9cd61d22f2825931.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/438a9eb2590543ad9cd61d22f2825931"}}, "title": "Prediction of the Human Pharmacokinetics of 30 Modern Antibiotics Using the ANDROMEDA Software", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2023-03-29", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2023.03.28.534601", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:45:02.021Z", "modified": "2026-08-20T10:45:02.045Z"}, {"entity": "publication", "iuid": "f032e441836b43bca398fcd413deaa0d", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/f032e441836b43bca398fcd413deaa0d.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/f032e441836b43bca398fcd413deaa0d"}}, "title": "Application of the ANDROMEDA Software for Prediction of the Human Pharmacokinetics of Modern Anticancer Drugs", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2023-03-21", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2023.03.18.533259", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:44:26.582Z", "modified": "2026-08-20T10:44:26.645Z"}, {"entity": "publication", "iuid": "e9dc245749e64771a8012b6eb55c450b", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/e9dc245749e64771a8012b6eb55c450b.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/e9dc245749e64771a8012b6eb55c450b"}}, "title": "In Silico Prediction of Human Clinical Pharmacokinetics with ANDROMEDA by Prosilico: Predictions for an Established Benchmarking Data Set, a Modern Small Drug Data Set, and a Comparison with Laboratory Methods.", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J"}, {"family": "Spjuth", "given": "Ola", "initials": "O"}], "type": "journal article", "published": "2023-01-00", "journal": {"title": "Altern Lab Anim", "issn": "0261-1929", "volume": "51", "issue": "1", "pages": "39-54", "issn-l": null}, "abstract": "There is an ongoing aim to replace animal and in vitro laboratory models with in silico methods. Such replacement requires the successful validation and comparably good performance of the alternative methods. We have developed an in silico prediction system for human clinical pharmacokinetics, based on machine learning, conformal prediction and a new physiologically-based pharmacokinetic model, i.e. ANDROMEDA. The objectives of this study were: a) to evaluate how well ANDROMEDA predicts the human clinical pharmacokinetics of a previously proposed benchmarking data set comprising 24 physicochemically diverse drugs and 28 small drug molecules new to the market in 2021; b) to compare its predictive performance with that of laboratory methods; and c) to investigate and describe the pharmacokinetic characteristics of the modern drugs. Median and maximum prediction errors for the selected major parameters were ca 1.2 to 2.5-fold and 16-fold for both data sets, respectively. Prediction accuracy was on par with, or better than, the best laboratory-based prediction methods (superior performance for a vast majority of the comparisons), and the prediction range was considerably broader. The modern drugs have higher average molecular weight than those in the benchmarking set from 15 years earlier (ca 200 g/mol higher), and were predicted to (generally) have relatively complex pharmacokinetics, including permeability and dissolution limitations and significant renal, biliary and/or gut-wall elimination. In conclusion, the results were overall better than those obtained with laboratory methods, and thus serve to further validate the ANDROMEDA in silico system for the prediction of human clinical pharmacokinetics of modern and physicochemically diverse drugs.", "doi": "10.1177/02611929221148447", "pmid": "36572567", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T12:17:05.423Z", "modified": "2026-08-20T12:17:05.485Z"}, {"entity": "publication", "iuid": "efb05666f75047dbb6c6893925a5e478", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/efb05666f75047dbb6c6893925a5e478.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/efb05666f75047dbb6c6893925a5e478"}}, "title": "Predicting the Influence of Fat Food Intake on the Absorption and Systemic Exposure of Small Drugs using ANDROMEDA by Prosilico Software", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-12-08", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.12.05.519072", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:42:43.012Z", "modified": "2026-08-20T10:42:43.074Z"}, {"entity": "publication", "iuid": "ddf9204b92c84e9eaf02591a3a60b5e9", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/ddf9204b92c84e9eaf02591a3a60b5e9.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/ddf9204b92c84e9eaf02591a3a60b5e9"}}, "title": "Predicting Gastrointestinal Absorption of Prodrugs and their Drugs with the ANDROMEDA by Prosilico Software", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-11-25", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.11.23.517725", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:42:23.960Z", "modified": "2026-08-20T10:42:24.034Z"}, {"entity": "publication", "iuid": "642cbb4bf4624cbfa4c9c8f67f8d7f21", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/642cbb4bf4624cbfa4c9c8f67f8d7f21.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/642cbb4bf4624cbfa4c9c8f67f8d7f21"}}, "title": "Validation of predicted conformal intervals for prediction of human clinical pharmacokinetics", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-11-13", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.11.10.515917", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:42:07.937Z", "modified": "2026-08-20T10:42:08.004Z"}, {"entity": "publication", "iuid": "78937eb8e2034637a0fed2c0afd5c7c1", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/78937eb8e2034637a0fed2c0afd5c7c1.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/78937eb8e2034637a0fed2c0afd5c7c1"}}, "title": "ANDROMEDA by Prosilico Software Successfully Predicts Human Clinical Pharmacokinetics of 300 Drugs Out of Reach for In Vitro Methods", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-10-07", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.10.05.511015", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:41:29.746Z", "modified": "2026-08-20T10:41:29.775Z"}, {"entity": "publication", "iuid": "aa8e48f252444cd0b97bc4da41b8023e", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/aa8e48f252444cd0b97bc4da41b8023e.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/aa8e48f252444cd0b97bc4da41b8023e"}}, "title": "Prediction and Classification of the Uptake and Disposition of Antidepressants and New CNS-Active Drugs in the Human Brain using the ANDROMEDA by Prosilico Software and Brainavailability-Matrix", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-09-30", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.09.28.509936", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:41:05.137Z", "modified": "2026-08-20T10:41:05.204Z"}, {"entity": "publication", "iuid": "90f286c509c84bb3ac718e943210f2b1", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/90f286c509c84bb3ac718e943210f2b1.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/90f286c509c84bb3ac718e943210f2b1"}}, "title": "Prediction of Biopharmaceutical Characteristics of PROTACs using the ANDROMEDA by Prosilico Software", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-09-23", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.09.22.509053", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:14:28.713Z", "modified": "2026-08-20T10:14:28.787Z"}, {"entity": "publication", "iuid": "cc33d1b63a774d84a5d3e704fc120122", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/cc33d1b63a774d84a5d3e704fc120122.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/cc33d1b63a774d84a5d3e704fc120122"}}, "title": "Using the ANDROMEDA by Prosilico Software for Prediction of the Human Pharmacokinetics of 4 Compounds of Natural Origin - Colistin, Curucumin, UCN-01 and Voclosporin", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J", "orcid": "0000-0002-8682-7206", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9415021fa24f47cf88a63d0cf805940c.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "posted-content", "published": "2022-08-17", "journal": {"issn-l": null}, "abstract": null, "doi": "10.1101/2022.08.17.504228", "pmid": null, "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T10:13:51.730Z", "modified": "2026-08-20T10:13:51.783Z"}, {"entity": "publication", "iuid": "aac32256fe0f4fbda1a6d76407104620", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/aac32256fe0f4fbda1a6d76407104620.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/aac32256fe0f4fbda1a6d76407104620"}}, "title": "In silico predictions of the human pharmacokinetics/toxicokinetics of 65 chemicals from various classes using conformal prediction methodology.", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J"}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "journal article", "published": "2022-02-00", "journal": {"title": "Xenobiotica", "issn": "1366-5928", "volume": "52", "issue": "2", "pages": "113-118", "issn-l": "0049-8254"}, "abstract": "Pharmacokinetic/toxicokinetic (PK/TK) information for chemicals in humans is generally lacking. Here we applied machine learning, conformal prediction and a new physiologically-based PK/TK model for prediction of the human PK/TK of 65 chemicals from different classes, including carcinogens, food constituents and preservatives, vitamins, sweeteners, dyes and colours, pesticides, alternative medicines, flame retardants, psychoactive drugs, dioxins, poisons, UV-absorbents, surfactants, solvents and cosmetics.About 80% of the main human PK/TK (fraction absorbed, oral bioavailability, half-life, unbound fraction in plasma, clearance, volume of distribution, fraction excreted) for the selected chemicals was missing in the literature. This information was now added (from in silico predictions). Median and mean prediction errors for these parameters were 1.3- to 2.7-fold and 1.4- to 4.8-fold, respectively. In total, 59 and 86% of predictions had errors <2- and <5-fold, respectively. Predicted and observed PK/TK for the chemicals was generally within the range for pharmaceutical drugs.The results validated the new integrated system for prediction of the human PK/TK for different chemicals and added important missing information. No general difference in PK/TK-characteristics was found between the selected chemicals and pharmaceutical drugs.", "doi": "10.1080/00498254.2022.2049397", "pmid": "35238270", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T09:33:03.556Z", "modified": "2026-08-20T09:33:53.690Z"}, {"entity": "publication", "iuid": "7cb94c0eb2714ab0bcc93fc7cb403eeb", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/7cb94c0eb2714ab0bcc93fc7cb403eeb.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/7cb94c0eb2714ab0bcc93fc7cb403eeb"}}, "title": "In silico prediction of volume of distribution of drugs in man using conformal prediction performs on par with animal data-based models.", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}, {"family": "Alvarsson", "given": "Jonathan", "initials": "J"}, {"family": "Arvidsson McShane", "given": "Staffan", "initials": "S"}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}], "type": "journal article", "published": "2021-12-00", "journal": {"title": "Xenobiotica", "issn": "1366-5928", "volume": "51", "issue": "12", "pages": "1366-1371", "issn-l": "0049-8254"}, "abstract": "Volume of distribution at steady state (Vss) is an important pharmacokinetic endpoint. In this study we apply machine learning and conformal prediction for human Vss prediction, and make a head-to-head comparison with rat-to-man scaling, allometric scaling and the Rodgers-Lukova method on combined in silico and in vitro data, using a test set of 105 compounds with experimentally observed Vss.The mean prediction error and % with <2-fold prediction error for our method were 2.4-fold and 64%, respectively. 69% of test compounds had an observed Vss within the prediction interval at a 70% confidence level. In comparison, 2.2-, 2.9- and 3.1-fold mean errors and 69, 64 and 61% of predictions with <2-fold error was reached with rat-to-man and allometric scaling and Rodgers-Lukova method, respectively.We conclude that our method has theoretically proven validity that was empirically confirmed, and showing predictive accuracy on par with animal models and superior to an alternative widely used in silico-based method. The option for the user to select the level of confidence in predictions offers better guidance on how to optimise Vss in drug discovery applications.", "doi": "10.1080/00498254.2021.2011471", "pmid": "34845977", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T09:33:01.905Z", "modified": "2026-08-20T09:33:52.045Z"}, {"entity": "publication", "iuid": "38f6c87d66fc491183166112b7bab275", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/38f6c87d66fc491183166112b7bab275.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/38f6c87d66fc491183166112b7bab275"}}, "title": "Comparison between lab variability and in silico prediction errors for the unbound fraction of drugs in human plasma.", "authors": [{"family": "Fagerholm", "given": "Urban", "initials": "U", "orcid": "0000-0001-6300-359X", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/8f579134421e480f88c871925505812b.json"}}, {"family": "Spjuth", "given": "Ola", "initials": "O", "orcid": "0000-0002-8083-2864", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/2c192389f99d4801b91f3350e07dfb9e.json"}}, {"family": "Hellberg", "given": "Sven", "initials": "S"}], "type": "journal article", "published": "2021-10-00", "journal": {"title": "Xenobiotica", "issn": "1366-5928", "volume": "51", "issue": "10", "pages": "1095-1100", "issn-l": "0049-8254"}, "abstract": "Variability of the unbound fraction in plasma (fu) between labs, methods and conditions is known to exist. Variability and uncertainty of this parameter influence predictions of the overall pharmacokinetics of drug candidates and might jeopardise safety in early clinical trials. Objectives of this study were to evaluate the variability of human in vitro fu-estimates between labs for a range of different drugs, and to develop and validate an in silico fu-prediction method and compare the results to the lab variability.A new in silico method with prediction accuracy (Q2) of 0.69 for log fu was developed. The median and maximum prediction errors were 1.9- and 92-fold, respectively. Corresponding estimates for lab variability (ratio between max and min fu for each compound) were 2.0- and 185-fold, respectively. Greater than 10-fold lab variability was found for 14 of 117 selected compounds.Comparisons demonstrate that in silico predictions were about as reliable as lab estimates when these have been generated during different conditions. Results propose that the new validated in silico prediction method is valuable not only for predictions at the drug design stage, but also for reducing uncertainties of fu-estimations and improving safety of drug candidates entering the clinical phase.", "doi": "10.1080/00498254.2021.1964044", "pmid": "34346291", "labels": [], "xrefs": [], "notes": [], "created": "2026-08-20T09:32:59.901Z", "modified": "2026-08-20T09:33:41.392Z"}]}