Atul Mohindra
Head of R&D Biologics
Atul joined Lonza in 2005 and has held various positions within the company. Today, as Head of Biologics R&D, he is responsible for leading a global innovation team of more than 150 people in the discovery, design and development of innovative biologics platforms, processes and technologies for Lonza's mammalian and microbial network. With over 20 years of experience in cell biology, bioprocessing and media optimization, Atul has successfully developed and implemented mammalian cell culture, purification and analytical platform processes for several innovator and biosimilar programs.
Come and join us to enable a healthier world.
Why Partner with Us
We offer our technology partners the path to accelerate the development of their innovative ideas and findings through:
Our Partnership Models
We look forward to working together
External Innovation at Lonza
Mammalian Expression Systems - areas of interest
Cell optimization
HTP screening
Synthetic biology
- Optimization strategies to improve productivity / the use of cell resources
- High throughput screening technologies for cell/clone identification (stability and productivity)
- Cell line stability solutions
- Cell line screening technologies
- System biology and synthetic biology tools
- Prediction tools (AI and ML) for clone/strain development and selection
Microbial Expression Systems - areas of interest
Strain optimization
Inclusion bodies
Secretion
Screening
- Strain stability improvements throughout the upscaling process
- Optimization of production of protein of interest / plasmid optimization
- Solutions around inclusion body formation
- Protein secretion technologies
- HT live strain screening and analysis tools
- Synthetic biology tools
- Prediction tools (AI and ML) for clone/strain development and selection
mRNA - areas of interest
Transcription, processing, purification
LNP formulation platform development
Delivery and targeting
Formulations
- LNP formulation platform development
Targeting
- Targeting and mRNA delivery
Manufacturing
- mRNA transcription, processing and purification
Bioconjugates (ADCs) - areas of interest
Bioconjugation
Linkers and payloads
Manufacturing
Conjugation Technologies
- Bioorthogonal conjugations
- Selective chemical conjugations
- ADC manufacturing using site selective conjugation (SSC)
- Specific conjugation technology for conjugation of oligonucleotides
Linkers and Payloads
- Novel mode of actions (MOA)
- New chemistries
Manufacturing Technologies
- High-throughput generation and analysis of bioconjugates at lab scale – and its potential applications in manufacturing
Bioprocess Development and Manufacturing - areas of interest
PAT
Downstream processing
Robotics automation
In-Silico modeling & Digital Twin tools
Miniaturization (microfluidics)
- PAT: Increase USP and DSP process monitoring and control with on-line and in-line analytical technologies
- Novel clarification and downstream platforms for new therapeutic modalities to accelerate time to clinic
- High throughput automation technologies for bioprocessing
- In-silico modeling and digital twin tools
- Manufacturing and technology transfer tools
Data Science and Bioinformatics - areas of interest
AI / Machine Learning
Algorithms to monitor biological processes
Bioinformatic tools for protein sciences
Data management
Gather Omics Knowledge
- Knowledge-bases of pathways in mammalian cells
- Omics datasets (genetics, genomics, proteomics, epigenetics, single cells) of mammalian cells in a bioprocessing environment
Characterize Biological Processes (Mammalian/Microbial)
- Algorithms to perform multi-omics association studies and machine learning with special emphasis on decision trees
- Technologies to measure multiple omics cell characteristics simultaneously (e.g. protein and gene expression)
Protein Sciences
- Technologies and algorithms to predict protein properties based on sequence and structural data
- Tools to predict the best expression systems based on pre-defined protein features (size, glycosylation, etc.)
Bioprocessing
- Algorithms to harness online bioreactor measurements (e.g. Raman spectra)
- High-throughput screening
- Software for high-throughput phenotypic screening and monitoring or proteins and cells
Data Management
- Technologies to store, access, query and view large omics datasets
- Databases and database structures to store knowledge derived from our experiments (e.g. graph knowledge bases)