QSAR Model Development for Early Stage Screening of Monoclonal Antibody Therapeutics to Facilitate Rapid Developability
Total Page：16
File Type：pdf, Size：1020Kb
QSAR model development for early stage screening of monoclonal antibody therapeutics to facilitate rapid developability. Arathi Kizhedath (B.Tech, MSc.ir) Doctor of Philosophy Faculty of Science, Agriculture and Engineering School of Engineering February 2019 QSAR model development for early stage screening of monoclonal antibody therapeutics to facilitate rapid developability. Arathi Kizhedath Supervisor: Prof. Jarka Glassey Co-supervisor: Dr Simon Wilkinson School of Engineering, Newcastle University Institute of Cellular Medicine, Newcastle University October 2018 Abstract Monoclonal antibodies (mAbs) and related therapeutics are highly desirable from a biopharmaceutical perspective as they are highly target specific and well tolerated within the human system. Nevertheless, several mAbs have been discontinued or withdrawn based either on their inability to demonstrate efficacy and/or due to adverse effects. With nearly 80% of drugs failing in clinical development mainly due to lack of efficacy and safety there arises an urgent need for better understanding of biological activity, affinity, pharmacology, toxicity, immunogenicity etc. thus leading to early prediction of success/failure. In this study a hybrid modelling framework was developed that enabled early stage screening of mAbs. The applicability of the experimental methods was first tested on chemical compounds to assess the assay quality following which they were used to assess potential off target adverse effects of mAbs. Furthermore, hypersensitivity reactions were assessed using Skimune™, a non-artificial human skin explants based assay for safety and efficacy assessment of novel compounds and drugs, developed by Alcyomics Ltd. The suitability of Skimune™ for assessing the immune related adverse effects of aggregated mAbs was studied where aggregation was induced using a heat stress protocol. The aggregates were characterised by protein analysis techniques such as analytical ultra-centrifugation following which the immunogenicity tested using Skimune™ assay. Numerical features (descriptors) of mAbs were identified and generated using ProtDCal, EMBOSS Pepstat software as well as amino acid scales for different. Five independent and novel X block datasets consisting of these descriptors were generated based on the physicochemical, electronic, thermodynamic, electronic and topological properties of amino acids: Domain, Window, Substructure, Single Amino Acid, and Running Sum. This study describes the development of a hybrid QSAR based model with a structured workflow and clear evaluation metrics, with several optimisation steps, that could be beneficial for broader and more generic PLS modelling. Based on the results and observation from this study, it was demonstrated incremental improvement via selection of datasets and variables help in further optimisation of these hybrid models. Furthermore, using hypersensitivity and cross reactivity as responses and physicochemical characteristics of mAbs as descriptors, the QSAR models generated for different applicability domains allow for rapid early stage screening and developability. These models were validated with external test set comprising of proprietary compounds from industrial partners, thus paving way for enhanced developability that tackles manufacturing failures as well as attrition rates. i ii List of Publications Kizhedath, Arathi, Simon Wilkinson, and Jarka Glassey. "Applicability of predictive toxicology methods for monoclonal antibody therapeutics: status Quo and scope." Archives of toxicology 91.4 (2017): 1595-1612. Kizhedath, Arathi, Simon Wilkinson, and Jarka Glassey. "Applicability of Traditional In Vitro Toxicity Tests for Assessing Adverse Effects of Monoclonal Antibodies: A Case Study of Rituximab and Trastuzumab." Antibodies 7.3 (2018): 30. Kizhedath, Arathi, and Jarka Glassey. "The importance of critical quality attributes in Quality by Design for rapid bioprocess development strategies." European Pharmaceutical Review 22.6 (2017): 48-50. Udugama, Isuru A., Hannah Feldman, Simoneta Caño de las Heras, Arathi Kizhedath, Jesper Bryde-Jacobsen, Frans van den Berg, Seyed Soheil Mansouri, and Krist V. Gernaey. "BIOPRO World Talent Campus: A week of real world challenge for biotechnology post-graduate students." Education for Chemical Engineers 25 (2018): 1-8. Kizhedath, Arathi, Simon Wilkinson, and Jarka Glassey. “Assessment of hepatotoxicity and dermal toxicity of butyl paraben and methyl paraben using HepG2 and HDFn in vitro models.” Toxicology in Vitro 55 (2018) 108-115. Kizhedath, Arathi, Micael Karlberg, and Jarka Glassey “Cross interaction chromatography based QSAR model for early stage screening to facilitate enhanced developability of monoclonal antibody therapeutics.” Biotechnology Journal (2018) Accepted. List of major presentations Kizhedath, Arathi, Simon Wilkinson, and Jarka Glassey. “Hybrid modelling approaches for early stage screening of monoclonal antibodies based on safety for rapid mAb developability” ESBES 2018, Lisbon, Portugal. Kizhedath, Arathi, Simon Wilkinson, and Jarka Glassey. “Assessment of hepatotoxic and dermal toxicity effects of Parabens using HepG2 and HDFN in vitro models.” British Toxicological Society Annual Congress 2018, Newcastle Upon Tyne, United Kingdom. Kizhedath, Arathi, Simon Wilkinson, and Jarka Glassey. “Early toxicity prediction based on hybrid modelling.” BESIG Young Researchers Meeting, IChemE, 2016, Dublin, Ireland. iii iv Acknowledgements The past three years have been a true learning experience for me, professionally and personally. This project was truly interesting and challenging. I also had the opportunity to broaden my horizons and get exposed to new perspectives in pharmaceutical safety testing strategies via conferences, training and outreach activities. Firstly, I would like to thank my extremely supportive supervisor, Prof Jarka Glassy without whom this dissertation would not be possible. I would also like to extend my gratitude to Dr Simon Wilkinson who co-supervised my work. Their patient guidance, enthusiastic encouragement and useful critiques helped shape up this dissertation. I would also like to acknowledge my colleague, Micael Karlbeg for the collaborative work on descriptor generation. I would also like to thank him for his professional and personal support throughout my PhD. In Chapter 4, Skimune™ assay was used to assess immunogenicity of aggregated mAbs and this was done by Alcyomics Ltd. I would like to thank Prof Anne Dickinson, Dr. Shaheda Ahmed and Ana Ribeiro for their support. In Chapter 7, MAb Fab structures were generated by João Victor de Souza Cunha and Dr Agnieszka Bronowska, School of Natural and Environmental Sciences, Newcastle University. I would like to thank them for them as well as Dr Milan Mijajlovic for their time and valuable academic discussions. I would like to thank all the Early stage researchers and Scientist in charge of the BIORAPID consortium. This project is a part of the BIORAPID consortium which has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie actions grant agreement No. 643056. I gratefully acknowledge this funding provided by the European Commission.I would like to thank Mr. Paul Sterling for his assistance in the Biolab. I would also like to thank Dr Achim Treumann and Dr Alexandra Solovyova from the Newcastle University Protein and Proteome Analysis (NUPPA) unit for their services on the Analytical Ultracentrifugation used in Chapter 4. I would also like to acknowledge Dr Andrew Filby from the Newcastle University Flow Cytometry Core Facility for the Cell Cycle analysis services used in Chapter 2. Last but not the least, I extend my heartfelt gratitude to my parents, brother, husband and friends whose continued support kept me motivated throughout my research period. v vi Table of contents Chapter 1. Applicability of predictive toxicology methods for monoclonal antibody 1 therapeutics: Status Quo and Scope 1.1.Aims and objectives 3 1.2. Mabs: Safety pharmacology and side effects 4 1.3. Quality by Design in mAb developability 14 1.4. In vitro systems for toxicity testing 16 1.5. In silico tools for predictive toxicology 18 1.6. Predictive Model Development 21 1.5.1. Databases 22 1.5.2. Descriptor Generation and model development: 23 1.5.3. Models 23 1.5.4. Validation 25 1.7. Scope of the study 25 Chapter 2. Assessment of hepatotoxicity and dermal toxicity of butyl paraben and 26 methyl paraben using HepG2 and HDFn in vitro models 2.1. Materials and Methods 28 2.1.1. Cell lines and reagents 28 2.1.2. Cell culture and maintenance 28 2.1.3. Cell seeding and treatment 28 2.1.4. WST-1 cell proliferation Assay 29 2.1.5. CellTiter-Glo® Luminescent Cell Viability Assay 29 2.1.6. GSH-Glo™ Glutathione Assay 29 2.1.7. Detection of Reactive oxygen species 30 2.1.8. Cell cycle Analysis 30 2.1.9. Mitochondrial Membrane Potential Assay 30 2.1.10. Statistical analysis 31 2.2. Results 31 2.2.1. Paraben induced cytotoxicity 31 2.2.2. Paraben induced reduction in ATP levels 31 2.2.3. Paraben induced reduction in glutathione levels 32 2.2.4. Paraben induced time dependent decrease in ATP levels 35 2.2.5. Cell cycle analysis to assess genotoxicity of parabens 36 2.2.6. Paraben induced Oxidative stress and mitochondrial dysfunction 38 2.3. Discussion 41 2.4. Chapter summary 44 Chapter 3 Applicability of traditional and novel in vitro toxicity tests for assessing 45 adverse effects of monoclonal antibodies: A case study of rituximab and