Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Joakim, Nyberg"'
Autor:
E. Niclas Jonsson, Joakim Nyberg
Publikováno v:
CPT: Pharmacometrics & Systems Pharmacology, Vol 13, Iss 8, Pp 1297-1308 (2024)
Abstract The full random‐effects model (FREM) is an innovative and relatively novel covariate modeling technique. It differs from other covariate modeling approaches in that it treats covariates as observations and captures their impact on model pa
Externí odkaz:
https://doaj.org/article/cde62fc5c2f84b00a885b4ff89bbc993
Autor:
E. Niclas Jonsson, Joakim Nyberg
Publikováno v:
CPT: Pharmacometrics & Systems Pharmacology, Vol 13, Iss 5, Pp 743-758 (2024)
Abstract The inclusion of covariates in pharmacometric models is important due to their ability to explain variability in drug exposure and response. Clear communication of the impact of covariates is needed to support informed decision making in cli
Externí odkaz:
https://doaj.org/article/3037db05927e472db168f831761c0c15
Autor:
Martin Geroldinger, Johan Verbeeck, Andrew C. Hooker, Konstantin E. Thiel, Geert Molenberghs, Joakim Nyberg, Johann Bauer, Martin Laimer, Verena Wally, Arne C. Bathke, Georg Zimmermann
Publikováno v:
Orphanet Journal of Rare Diseases, Vol 18, Iss 1, Pp 1-12 (2023)
Abstract Background Recommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set
Externí odkaz:
https://doaj.org/article/4f9b12e7fc3f4ae699a506a509e41b49
Autor:
E. Niclas Jonsson, Joakim Nyberg
Publikováno v:
CPT: Pharmacometrics & Systems Pharmacology, Vol 11, Iss 6, Pp 673-686 (2022)
Abstract Understanding the uncertainty in parameter estimates or in derived secondary variables is important in all data analysis activities. In pharmacometrics, this is often done based on the standard errors from the variance–covariance matrix of
Externí odkaz:
https://doaj.org/article/2f02b8810ba948c5b0fb5bb0ef8b6ff5
Publikováno v:
CPT: Pharmacometrics & Systems Pharmacology, Vol 11, Iss 2, Pp 149-160 (2022)
Abstract The full random‐effects model (FREM) is a method for determining covariate effects in mixed‐effects models. Covariates are modeled as random variables, described by mean and variance. The method captures the covariate effects in estimate
Externí odkaz:
https://doaj.org/article/cfdd6f37365e48f9b90e4f2ed76ad75a
Autor:
Lina Keutzer, Huifang You, Ali Farnoud, Joakim Nyberg, Sebastian G. Wicha, Gareth Maher-Edwards, Georgios Vlasakakis, Gita Khalili Moghaddam, Elin M. Svensson, Michael P. Menden, Ulrika S. H. Simonsson, on behalf of the UNITE4TB Consortium
Publikováno v:
Pharmaceutics, Vol 14, Iss 8, p 1530 (2022)
Pharmacometrics (PM) and machine learning (ML) are both valuable for drug development to characterize pharmacokinetics (PK) and pharmacodynamics (PD). Pharmacokinetic/pharmacodynamic (PKPD) analysis using PM provides mechanistic insight into biologic
Externí odkaz:
https://doaj.org/article/25a790d93aeb473e9a0152c76324f8f0
Autor:
Wenyuan Xiong, Sofia Friberg Hietala, Joakim Nyberg, Orestis Papasouliotis, Andreas Johne, Karin Berghoff, Kosalaram Goteti, Jennifer Dong, Pascal Girard, Karthik Venkatakrishnan, Rainer Strotmann
Publikováno v:
Cancer chemotherapy and pharmacology. 90(1)
Purpose Tepotinib is a highly selective MET inhibitor approved for treatment of non-small cell lung cancer (NSCLC) harboring METex14 skipping alterations. Analyses presented herein evaluated the relationship between tepotinib exposure, and efficacy a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::464924710d847b007073a7687056d495
https://pubmed.ncbi.nlm.nih.gov/35771259
https://pubmed.ncbi.nlm.nih.gov/35771259
Autor:
Chris Rackauckas, Yingbo Ma, Andreas Noack, Vaibhav Dixit, Patrick Kofod Mogensen, Chris Elrod, Mohammad Tarek, Simon Byrne, Shubham Maddhashiya, José Bayoán Santiago Calderón, Michael Hatherly, Joakim Nyberg, Jogarao V.S. Gobburu, Vijay Ivaturi
AO_SCPLOWBSTRACTC_SCPLOWPharmacometric modeling establishes causal quantitative relationship between administered dose, tissue exposures, desired and undesired effects and patients risk factors. These models are employed to de-risk drug development a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::156196046cd96eefe80f9ca7dba04f98
https://doi.org/10.1101/2020.11.28.402297
https://doi.org/10.1101/2020.11.28.402297
Publikováno v:
Anesthesiology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::9f91d24a42657f4667caf749c9985cde
https://pubmed.ncbi.nlm.nih.gov/32472802
https://pubmed.ncbi.nlm.nih.gov/32472802
Publikováno v:
Anesthesiology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6f7f8c05a81bb2016e2eab4c296f575
https://doi.org/10.1097/aln.0000000000003211
https://doi.org/10.1097/aln.0000000000003211