Automating Chemical Synthesis Through Flow Chemistry

Transcription

1 Automating Chemical Synthesis Through Flow Chemistry eal Sach Senior Principal Scientist ncology Medicinal Chemistry Science Centre Drive La Jolla, CA 92130, USA 1 st RSC/SCI Symposium on Continuous Processing and Flow Chemistry GSK Stevenage, UK Thursday 4 th ovember 2010

2 Contents Conjure Flow Reactor Applications and Examples of Conjure Flow Reactor to Discovery and Development Towards Automated Synthesis

3 Flow - Key Applications to Drug Discovery Medicinal - Expanding Chemical Space Forbidden chemistries Library synthesis Extending temperature ranges (vs. microwave) Process - Enabling and Economics Scaling Forbidden chemistries (diazotation etc.) Scale-up of Discovery microwave chemistry Minimised scale-up considerations Stability Reactivity Substrates not accessible using traditional chemical synthesis techniques Early implementation of flow chemistry can significantly ease the transitions from Discovery to Process

4 Flow Chemistry Limitations Emerging Technology (at laboratory scale) Heterogeneous Reactions Material Requirements Time Requirements 2004 Collaboration started with Wyeth and Accendo Analytical Scale=0.5ml/min (HPLC like flow rates) nano micro meso kilo lab pilot plant manufacturing

5 Schematic Draw from up to 4 of 36 source vials Fluid Prep Feed (working solvent) mix Discovery Library synthesis (vary monomers) Process ptimization (vary conditions) interface Discrete segments inserted and maintained in main flow Reactor temperature ote mixing is uniquely independent of flow rate Analytics and sample collection

6 Adding Artificial Intelligence ne-size-fits-all initial conditions Library elements (Discovery) Reaction Conditions (Process) (flowing segments) Greater percentage of successful library elements (discovery). ptimized reactions (process) m n Pass? Fail? Collect via Fraction Collector (Discovery) Prep via repetitive segments (Process) l HPLC/MS Product Y/? Yield & Purity L H DE calculates best conditions L H Vary prescribed reaction parameters around initial conditions. Automatically done based on Simplex and DE statistical optimization tools.

7 Conjure Flow Path Sample Dilutor Feed module Reactor module HPLC stack ELSD MS Sample Dilutor Detail Fraction collector Fluid prep module utput flow from Reactor

8 Conjure Square-Wave Reaction Segments Total Segment Size uL. Typically 300uL, 5mg Substrate Carrier Solvent 50uL He or FL 300uL Reaction Mixture 50uL He or FL Carrier Solvent Multiple Segments Active Within Reactor (up to 4) Each peak is a 5mg reaction Exact Stoichiometry (fluid prep) Exact Reaction Time (flow rate) Exact Temperature (within 0.1C) mau DAD1 E, Sig=310,2 Ref=off (70807A\6X6X3TEMPACC \ D) Peaks n Scale Bubble or UV Detection o Dead Reckoning min Heart cut is sampled and directed for LC/MS Analysis (ultra-fast gradients <2min run-times). Enables real-time results between segments. o contamination between reaction segments, key.

9 Sampling Heart Cuts from the Flowing Segments Primary flow from reactor Sample loop Collection or waste 20 L Mixer tube HPLC flow HPLC column 5 L Injection loop Waste Dilution syringe 2500 L Sample syringe 25 L Sample Dilutor Module Solvent

10 Sampling Heart Cuts from the Flowing Segments Primary flow from reactor Sample loop Collection or waste Mixer tube HPLC flow HPLC column Injection loop Waste Dilution syringe 2500 L Sample syringe 25 L Mixing with Diluent Solvent

11 Sampling Heart Cuts from the Flowing Segments Primary flow Primary flow Sample loop Mixer tube HPLC flow HPL C flow Injection loop Waste Dilution syringe 2500 L Sample syringe 25 L Return Injecting onto HPLC Solvent

12 Demonstration S Ar Library Preparation R2 R1 R4 X 1 X 2 H R2 R1 R4 R3 X MP R3 X X 2 X=C-2 or + H X 1 6 Amines x 6 Aryls = 36 Library 0.5M Solutions 100uL Each Total Segment Volume = 300uL 3 Temperatures 150 C, 200 C, 250 C 10 Minute Reaction Time MP Carrier Solvent 108 Experiments = 15 hours Run n-line HPLC/UV/MS/ELSD Analysis Hamper, Bruce C.; Tesfu, Eden. Direct uncatalyzed amination of 2-chloropyridine using a flow reactor. Synlett (2007), (14),

13 C in-situ Yield by 254nm HPLC/MS Analysis 150 C - 42% 200 C - 61% 250 C - 22% verall Library Success Rate : 88%

14 Demonstration Singleton DE ptimisation for Process 3 Level 2 Factor Design Temp 100 C, 150 C, 200 C Equivalents 1eq. 2eq. 3eq. H MP + H 11 Reactions 13-20mg each 2 Centre Points mau DAD1 A, Sig=254,2 Ref=off (70809B\DEACC \ D) Total = 184mg Total Time = 116 minutes Vial 8 1-Vial 9 1-Vial 10 1-Vial 11 1-Vial 12 1-Vial 13 1-Vial 14 1-Vial 15 1-Vial 16 1-Vial C 150 C 200 C 1-Vial min 50 C 5min 50 C 5min

15 Demonstration Singleton DE ptimisation for Process Investigation: 3,4,5-Trichloropyridine ptimisation (MLR) Yield with Experiment umber labels Temp Equivalents Yield bserved bserved 70 y=1*x+7.531e-006 R2= Investigation: 3,4,5-Trichloropyridine Predicted ptimisation (MLR) Contour Plot =11 R2=0.996 R2 Adj.=0.993 DF=5 Q2=0.961 RSD= Yield MDDE 7-8/14/ :25:40 AM

16 Issues Flow De-Carboxylation H H -C2 IPA Extreme temperatures Extreme pressures ot possible in batch Flow Experimental Accendo DE optimization completed in 1hr CCC Design 15 experiments H Knife edge optimal conditions 275 C, 2000psi, 15 minutes >50% product p Sharp Decrease in Yield 15 min Time Conclusions Key template accessed IP free chemical space Substrate of interest to multiple TA s Flow processes are scalable min 200 C Temp C Sharp Decrease in Yield

17 Triazoles and ick Chemistry Triazoles Metabolically stable pieces Significantly lower logd of a potential drug molecule (improved ADME properties) 1,4-substituted-1,2,3-triazoles can be easily prepared in excellent yield using ick Chemistry R1 R3 R2 3 R1 CuS 4 (0.05eq.) aascorbate (0.1eq.) t BuH / H 2 R2 R3 ick Chemistry Advantages Extremely fast, clean reactions Installing acetylenes in drug molecules is convergent with existing and common halide intermediates Functional group tolerance enables diverse pieces to be stitched together Disadvantages Preparing low MW organic azides is extremely dangerous in batch Kolb, Hartmuth C.; Finn, M. G.; Sharpless, K. Barry. ick chemistry: diverse chemical function from a few good reactions. Angewandte Chemie, International Edition (2001), 40(11),

18 Triazole ick Chemistry Azide Formation Can we prepare low MW azides in-situ from halides and a 3 in flow? R1 X=, Br or I H Br R3 0.25M R2 X a a 3 (1eq.) 3 (1eq.) DMF / H 2 10:1 150 o C / 5min + ax + ax R2 R3 H The click reaction is known to work with extremely low concentrations of Cu R1 Conditions DMF / Water required for a 3 solubility and solubility of triazole products 2hr Accendo DE ptimization 5min 175 C >75% y

19 Scope of in situ ick Chemistry H H Alkyl Halides 1, 72 % 2, 28 % 3, 72 % 4, 43% 5, 61% 6, 50% Br I Terminal Acetylenes H Br H 0.25M a 3 (1eq.) DMF / H 2 10:1 150 C / 5min 7, 70 % 13, 30 % 8, 40 % 14, 76 % H 9, 60 % H 15, 39 % 10, 72 % 16, 63 % 11, 88 % H H 12, 46 % 17, 60 % Flow Cu Reactor 18, 51 % 19, 72 % 20, 92 % H H 21, 26 % 22, 63 % H H 23, 77 % 24, 50 % 25, 32 % 26, 21% 27, 47 % H 28, 58 % 29, 65 % 30, 50 % Bogdan, Andrew R.; Sach, eal W. The use of copper flow reactor technology for the continuous synthesis of 1,4-disubstituted 1,2,3-triazoles. Advanced Synthesis & Catalysis (2009), 351(6),

20 Butyne Sonogashira Br I + Issues Pd(P(Ph) 3 ) 4 DIPEA EtH/Dioxane "Cu" Butyne b.p. 8 C Br Pressurized system Dangerous in batch Selectivity challanges Flow Experimental Accendo optimization completed in 2hrs Demonstrates 125 C as optimal for conversion/time Cu Reactor 125C, 4 min. Hastalloy Reactor 125C, 4 min. Conclusions SM SM Product Product Scalable process (24g/day) Cu reactor removes requirements for Cu additive 1.2g delivered to project team

21 Production Mode Reproduce automatically optimized chemistry Scale out not up, as a function of time D A D 1 E, S ig= 310,2 R ef= off ( A :\F L W _C H... W _C H E M I S TR Y _246C L_D E \R EPEATSACC \ D ) m A U min 1hour 1day 1week mg 3g 72g 0.5kg

22 The ext Step Automated DE ptimization DE Software osing this loop enables automated reaction optimization Data Collation and Interpretation Reagents Database Design Wizard Instrument Control HPLC/MS Analysis elb

23 The ext Step Automated DE ptimization Automated ptimization Set initial DE space Set theoretical parameter space Set objective (LC/MS) Enable Automated Simplex ptimization Iteration 1 Iteration 2 Iteration 3 bjective Met System automatically scales chemistry using optimized conditions L H L L H H

24 Conclusions Demonstrated Preparation of discreet square wave reaction segments Library optimization and enumeration (Discovery) Singleton optimization (Process) Singleton scale-out (Discovery and Process) Comment - We don t do flow, for flows sake ext steps Continue to identify forgotten chemistries (long forbidden) ose DE loop for automated optimization Multiple step synthesis

25 Acknowledgements Technology Joel Hawkins Jan Hughes (Accendo) Terry Long (Accendo) Kristin Price Larry Truesdale Chemistry Andrew Bogdan (Cornell) Valery Folkin (Scripps) Jason Hein (Scripps) Peter Huang Kevin Bunker Paul Richardson