Automation Coleen Robinson, AstraZeneca 2017 Annual Meeting of the - PowerPoint PPT Presentation

Engaging Scientists in the Adoption of Automation Coleen Robinson, AstraZeneca 2017 Annual Meeting of the Dial-a-Molecule Network

Why? 2

Agenda • Why Automation? • What is Effective Automation? • Importance of Equipment Evaluation • Automation at AZ • Range of Approaches • Range of Equipment • Range of Users. • Automation Adoption. 3

Increase productivity Why? Enabling unattended operation Increase throughput Minimising human intervention Produce higher quality data Obtain a greater density data And much more ………. 4

What is Effective Automation. 5

Importance of Equipment Evaluation • Understand costs vs benefits • Resource required • Engage end users • Support change management • Define specific configuration • Compare alternatives • Use real-case examples • Chemistries / processes • User groups 6

Can we automate a process from start to finish on one platform? 7

Aim • To evaluate the possibility to investigate process from start to end • Weighing / Work-up / Filtration • Use project examples • Investigate a number of experimental variables, using a statistically designed set of experiments DMA Pd-118, DIPEA, 2-Ethylaminoethanol tBuOH, Water 90°C 8

Fully Automated? N 2 120 Conversion (%) 100 80 60 40 20 0 Time (hr) 9

Planning and Data Reaction Analysis Liquid Design Interpretation Handling Preparation Addition and HPLC GC Conclusions Analytical data Statistical or Reaction UPLC Solid Handling Reporting Kinetic 10

Would chemists carry out a number of experiments in parallel if it was as easy as carrying out one? 11

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Do we want to carry out more experiments in parallel or collect more data from each experiment? • To investigate using Automated Lab Reactors (EasyMax/OptiMax) and associated software to automate part of the process of experimental write up and data capture. • LabConnect Trial on AZ project to: • Evaluate the ability of scientists to use the EasyMax as a Experimental personal reactor to carry out all chemical operations. Details and Data • To enable effective re-use of experimental details and data. • To work with vendor and other companies to direct and exploit the development of the software. • Engage scientists to help devise a fit for purpose solution. 14

Why? Increase in the number of parallel reactions? 100 18 90 16 Pre-Trial 80 14 Oct-14 70 12 Feb-15 60 10 50 8 40 6 30 4 20 2 10 0 0 Percentage Use of Percentage of Percentage of Work Number of Number of data Percentage of Mettler Equipment Reactions With One Carried Out in Automated Steps sources recorded Equipment Faults or More PAT Probe Parallel Per Experiment from each Experiment 15

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2006 2017 17

2006 2017 18

Generalist Specialist Data/information from each reaction Number of reactions Crystallisation Flow PAT Scale-Up Screening FED / DoE 19

Generalist Specialist Data/information from each reaction Number of reactions 20

Why? Automation Uptake 350 180 May – Nov 2016 150 160 300 Asymmetric SK233 130 H2 140 250 Amigo 110 TM- 120 catalysis screens 90 200 100 70 80 150 50 60 100 30 40 50 10 20 0 -10 0 21