Calero-Rubio C - Search Results

1

Machine Learning Feature Selection for Predicting High Concentration Therapeutic Antibody Aggregation.

Lai PK, Fernando A, Cloutier TK, Kingsbury JS, Gokarn Y, Halloran KT, Calero-Rubio C, Trout BL. Lai PK, et al. Among authors: calero rubio c. J Pharm Sci. 2021 Apr;110(4):1583-1591. doi: 10.1016/j.xphs.2020.12.014. Epub 2020 Dec 18. J Pharm Sci. 2021. PMID: 33346034

2

Machine Learning Applied to Determine the Molecular Descriptors Responsible for the Viscosity Behavior of Concentrated Therapeutic Antibodies.

Lai PK, Fernando A, Cloutier TK, Gokarn Y, Zhang J, Schwenger W, Chari R, Calero-Rubio C, Trout BL. Lai PK, et al. Among authors: calero rubio c. Mol Pharm. 2021 Mar 1;18(3):1167-1175. doi: 10.1021/acs.molpharmaceut.0c01073. Epub 2021 Jan 15. Mol Pharm. 2021. PMID: 33450157

3

A single molecular descriptor to predict solution behavior of therapeutic antibodies.

Kingsbury JS, Saini A, Auclair SM, Fu L, Lantz MM, Halloran KT, Calero-Rubio C, Schwenger W, Airiau CY, Zhang J, Gokarn YR. Kingsbury JS, et al. Among authors: calero rubio c. Sci Adv. 2020 Aug 5;6(32):eabb0372. doi: 10.1126/sciadv.abb0372. eCollection 2020 Aug. Sci Adv. 2020. PMID: 32923611 Free PMC article.

4

Relating Protein-Protein Interactions and Aggregation Rates From Low to High Concentrations.

Ghosh R, Calero-Rubio C, Saluja A, Roberts CJ. Ghosh R, et al. J Pharm Sci. 2016 Mar;105(3):1086-96. doi: 10.1016/j.xphs.2016.01.004. J Pharm Sci. 2016. PMID: 26928400

5

Predicting Protein-Protein Interactions of Concentrated Antibody Solutions Using Dilute Solution Data and Coarse-Grained Molecular Models.

Calero-Rubio C, Ghosh R, Saluja A, Roberts CJ. Calero-Rubio C, et al. J Pharm Sci. 2018 May;107(5):1269-1281. doi: 10.1016/j.xphs.2017.12.015. Epub 2017 Dec 21. J Pharm Sci. 2018. PMID: 29274822 Free PMC article.

6

A Systematic Approach to Evaluating Closed System Drug-Transfer Devices During Drug Product Development.

Patke S, Gaillat EN, Calero-Rubio C, Gooding TB, Audat H, Leman M, Filipe V, Saluja A. Patke S, et al. Among authors: calero rubio c. J Pharm Sci. 2022 May;111(5):1325-1334. doi: 10.1016/j.xphs.2021.12.020. Epub 2021 Dec 24. J Pharm Sci. 2022. PMID: 34958824

7

Electrostatically Mediated Protein-Protein Interactions for Monoclonal Antibodies: A Combined Experimental and Coarse-Grained Molecular Modeling Approach.

Ferreira GM, Calero-Rubio C, Sathish HA, Remmele RL Jr, Roberts CJ. Ferreira GM, et al. Among authors: calero rubio c. J Pharm Sci. 2019 Jan;108(1):120-132. doi: 10.1016/j.xphs.2018.11.004. Epub 2018 Nov 9. J Pharm Sci. 2019. PMID: 30419274

8

Predicting High-Concentration Interactions of Monoclonal Antibody Solutions: Comparison of Theoretical Approaches for Strongly Attractive Versus Repulsive Conditions.

Calero-Rubio C, Saluja A, Sahin E, Roberts CJ. Calero-Rubio C, et al. J Phys Chem B. 2019 Jul 11;123(27):5709-5720. doi: 10.1021/acs.jpcb.9b03779. Epub 2019 Jun 26. J Phys Chem B. 2019. PMID: 31241333

9

Coarse-Grained Antibody Models for "Weak" Protein-Protein Interactions from Low to High Concentrations.

Calero-Rubio C, Saluja A, Roberts CJ. Calero-Rubio C, et al. J Phys Chem B. 2016 Jul 14;120(27):6592-605. doi: 10.1021/acs.jpcb.6b04907. Epub 2016 Jul 1. J Phys Chem B. 2016. PMID: 27314827

10

Light Scattering to Quantify Protein-Protein Interactions at High Protein Concentrations.

Woldeyes MA, Calero-Rubio C, Furst EM, Roberts CJ. Woldeyes MA, et al. Among authors: calero rubio c. Methods Mol Biol. 2019;2039:23-37. doi: 10.1007/978-1-4939-9678-0_2. Methods Mol Biol. 2019. PMID: 31342416

Save citations to file

Email citations

Send citations to clipboard

Add to Collections

Add to My Bibliography

Create a file for external citation management software

Your saved search

Your RSS Feed

My Custom Filters

Publication date

Text availability

Article attribute

Article type

Article Language

Species

Sex

Age

Other

17 results

Search Page

Filters