Previous NATi Call for Proposals (Closed)

1.

Current designs for mRNA drug candidates are not sufficiently effective.

• Accelerate drug development through smart design
• Improve drug profile early in development

• A disease-agnostic algorithm (or a set of algorithms) to design linear and/or non-linear mRNA drugs, that achieves the following:
  • >6-fold increase of in vitro protein expression compared to benchmark sequences (i.e. approved drugs or clinical trial candidates)
  • >3-fold increase of in vivo expression, along with similar efficacy, durability, and safety compared to benchmark sequences, via intramuscular administration and separately via intravenous administration, using established delivery methods and validated assays
• Use of electronic laboratory notebooks to digitise and centralise management of experimental data, to facilitate downstream drug development

Optional

• Collaboration with data partners (e.g. industry) to test and validate new algorithm(s)
• Use of artificial intelligence and/or machine learning

1.

Limited access to bespoke chemistries and modifications impedes synthesis of hit compound libraries for siRNA/ASO drug development.

• Support hit compound synthesis
• Develop novel chemical modifications for siRNA and/or ASO drugs

• A robust, high-throughput workflow for oligonucleotide synthesis that achieves the following:
  • Ability to synthesise siRNA and ASO with a mixture of standard chemical modifications
  • Quality control demonstrating >80% purity and other standard quality attributes required for hit screening
  • Turnaround time of <2 weeks to generate a library of at least 96 distinct candidates each for siRNA and ASO
• At least 1 novel chemical modification to demonstrate at least one of the following improvements, using relevant in vitro and in vivo functional assays:
  • Increase potency
  • Extend duration of drug effect
  • Improve release into the cytosol
  • Reduce toxicity
• Use of electronic laboratory notebooks to digitise and centralise management of experimental data, to facilitate downstream drug development

Optional

• Collaboration with knowledge partners (e.g. industry) to test new chemistries
• Use of automation to increase throughput, streamline workflows, and/or reduce costs

1.

Lack of local production capacities and automation capabilities to accelerate the development of mRNA assets to clinical readiness

• Develop mRNA manufacturing and quality control capabilities to be routinely operated in compliance with GLP, with ability to adopt GMP-like operations on demand
• Develop automation strategies to improve consistency, reduce waste and increase turnaround time

• Demonstrate GLP production at sufficient yield and quality for preclinical studies
• Develop analytical workflows and control strategies to enable adoption of QbD framework
• Integrate unit operations to support end-to-end manufacturing
• Demonstrate quantified improvements over conventional processes

2.

Lack of local production capacities and automation capabilities to accelerate the development of siRNA/ ASO assets to clinical readiness

• Develop siRNA/ ASO manufacturing and quality control capabilities to be routinely operated in compliance with GLP, with ability to adopt GMP-like operations on demand
• Develop automation strategies to improve consistency, reduce waste and increase turnaround time

• Demonstrate GLP production at sufficient yield and quality for preclinical studies
• Develop analytical workflows and control strategies to enable adoption of QbD framework
• Integrate unit operations to support end-to-end manufacturing
• Demonstrate quantified improvements over conventional processes