8.00AM - 6.00PM EST | 5.00AM - 3.00PM PST

8:50 am Chair’s Opening Remarks

Enhancing Industrial Applications and Solving Scale-Up Issues with Biocatalysed Reactions – Transitioning Biocatalytic Approaches from Lab to Commercial Manufacturing

9:00 am Biocatalysis for Commodity and Speciality Chemistry

Synopsis

  • Overview of the state of the art on the most famous biocatalytic processes currently at the industrial scale.
  • Explore a focus on a particular industrial scale-up for producing huge quantities of a compound of interest.
  • Highlight current R&D development at a lab-scale.

9:30 am Relevance of process modeling to biocatalysis at pilot scale

Synopsis

  • Discuss how even an item as basic as enzyme kinetics is not always accurately known when scaling a process
  • Assess Pareto front modeling and evaluation, common in other areas of chemical processing, has not been very prevalent in biocatalytic processing
  • Evaluate how such modeling can drive decisions about options for process improvement, with examples

10:00 am Morning Networking Break

11:00 am Modifying Reaction Conditions to Enhancing Reactions and Avoiding Enzyme Engineering

  • Ryan Phelan Senior Scientist - Biocatalysis, Process Chem & Catalysis Group, AbbVie

Recent Advancements to Enhance Mature Reaction Classes

11:30 am Microbial lysyl oxidases: New Biocatalytic Tools for Chemical Biology, Materials Science And Beyond

  • Paul Race Professor - Biological Chemistry, University of Bristol

Synopsis

  • Learn how Lysyl oxidases (LOXs) catalyze the oxidative deamination of lysyl and hydroxylysyl groups, generating reactive aldehydes that undergo intermolecular cross-linking reactions
  • Discover how these enzymes are attractive candidates for use across a range of application areas, though their exploitation has been limited by challenges associated with their production at scale
  • Outline progress in the identification and recombinant production of LOXs from microbial sources, and describe examples of their use as tools in chemical biology tools and materials science

12:00 pm Lunch and Networking Break

1:00 pm Nitroreductase: Current Successes and Challenges at Amgen

Synopsis

  • Discuss what the industry has learned through the application of Nitroreductase technology over the last 2 years over a series of projects
  • Analyze the challenges that have been faced, the successes in the chemistry, and projections on where this technology is going

1:30 pm Late-Stage Chemoenzymatic Modifications of an FDAApproved Antibiotic

Synopsis

  • Uncover how Indole prenyltransferase (IPT) enzymes catalyze the transfer of prenyl groups from a native prenyl pyrophosphate donor to an indole-derived acceptor
  • Explore how IPTs have interesting promiscuity in terms of donors and acceptors allowing them to catalyze late-stage modifications of compounds.
  • Learn how to use a chemoenzymatic method involving different pyrophosphate substrates and IPTs to synthesize derivatives of an FDA-approved antibiotic, and how this makes derivatives possess superior antimicrobial activity compared to the parent compound.

2:00 pm Afternoon Break and Poster Session

Utilising Enzyme Engineering to Optimise Novel Biotransformations

3:00 pm Biocatalytic Toolbox for Site-Selective Insulin Modification

  • Chihui An Associate Principal Scientist, Merck & Co

Synopsis

  • Outline the efforts on developing a general enzymatic method to chemoselectively functionalize insulin to enable the discovery and commercial manufacturing of novel insulin therapeutics
  • Explore how to use enzyme evolution to evolve from a single enzyme parent, a “toolbox” of highly active and selective amidation enzymes that enable chemists to construct insulin analogs without laborious chromatographic purification
  • Evaluate how the enzymes from the toolbox were applied to large scale synthesis of a preclinical candidate to demonstrate application for commercial manufacturing

3:30 pm Deep Dive into Machine Learning Models For Directed- Evolution Of Enzymes

Synopsis

  • Discuss the increased interest in using machine learning to assist in enzyme redesign in the pharmaceutical industry
  • Benchmark the performance of prediction models built using an array of machine learning methods and protein descriptor types (sequence and structure-based) against a variety of datasets
  • Evaluate the results suggest that Convolution Neural Network models built with amino acid property descriptors could be the most widely applicable technique for enzyme reengineering

4:00 pm Chair’s Closing Remarks