The Experimental Approaches Applied to Optimise and Control a Cell-based Potency Assay used to Test a Live Attenuated Dengue Vaccine

Transcription

1 The Experimental Approaches Applied to Optimise and Control a Cell-based Potency Assay used to Test a Live Attenuated Dengue Vaccine Dr. Lee C. Smith BEBPA, Basel 26 Sept 2013

2 Topics Covered What is Dengue and the need for a vaccine The bioassay potency readout for DENVax The approach taken in assay development Selection & screening of assay parameters Optimisation of assay set points Assay precision analysis & assay transfer Assay preparation for phase III validation

3 Dengue Fever Tropical/sub-tropical disease 3

4 Dengue Fever Dengue is the most important mosquito-borne viral disease in the world affecting populations across Asia, Latin America and Africa 2 Annual infections In 2010 Estimated annual global burden of Dengue 400 million people infected 100 million develop clinical illness 500 thousand hospitalized 20 thousand deaths, mostly in children

5 Dengue Fever Over one half of world population threatened million dengue infections per year 36 million cases of dengue fever per year 2.1 million cases of dengue hemorrhagic fever > 20,000 deaths per year Mosquito-borne infection Four serotypes: DEN-1 through DEN-4 No therapeutic options No vaccine currently available Any vaccine candidate must protect against all four dengue serotypes 5

6 Zoonotic virus 1. Dengue fever 2. Dengue haemorrhagic fever * *Ab dependent enhancement (ADE)

7 4 Serotypes; all cause disease Any vaccine candidate must protect with neutralizing Abs against all four dengue serotypes 7

8 Measuring Vaccine Potency 8

9 Plaque Based Assays Plaque assays - standard for virus concentration A confluent cell monolayer is infected with the virus & covered with a semi-solid medium to prevent the virus infection from spreading indiscriminately A viral plaque is formed when a virus infects a cell within the fixed cell monolayer which will lyse and spread the infection to adjacent cells where the infection-to-lysis cycle is repeated The infected cell area will create a plaque (an area of infection surrounded by uninfected cells) which can be seen visually or with an optical microscope after 1 2 weeks 9

10 Immuno Focus Assay (IFA) Rapid variation of plaque assay Uses immunostaining with antibodies specific for the viral Ag Measure host cell infection before an actual plaque is formed. Shorter incubation period (e.g., 1-5 days) Stain with 2 Ab enzyme conjugates Substrate leads to coloured foci Results are expressed as Focus Forming Units or FFU/mL 10

11 => Spearman-Karber & Reed-Muench 11

12 Dengue Immuno Focus Assay (IFA) Relatively slow progress to distinct CPE Stain virus plaques with anti-dengue Abs after few days Count Focus Forming Units (FFU/mL)

13 A Perfect Spot? 13

14 We re counting spots so we wish them to be: Clean round spots Separated from others Unambiguous The Right Size 14

15 Imperfections Comets Too small Satellites Too big 15

16 An inability to count the foci = Inaccuracy & imprecision The method needs to produce foci that are the right size, not merged, have no comets or satellites regardless of who performs it, where it is performed and when it is performed 16

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18 DoE brings understanding which parameters have an effect upon the desired responses which parameters interact which parameters need to be focused upon and optimised and those that can be fixed The design space & how close to failure we operate the assay 18

19 System Variables Controllable (X) Factors System Response Measures Uncontrollable (N) Factors 19

20 Scoping - Assay Deconstruction Dilution series Overlay type Volume added Overlay conc Time Temp CO2 conc Incubation Vol Pressure Repeats Temp Vol PBS Wash conc Time Temp Blocking Mixing 2 o Ab Agitation Optional storage point Titer Comets Satellites Vol Time Temp CO2 conc Incubation temp vol Time Methanol fix Stop trigger with wash Inubation time Time uncovered Conc Vol Agitation Repeats AP Conc 20

21 Discuss & Agree what s important 21

22 Risk Assessment Control Strategy Heat Map Unit Operation Method Parameters Ranges or Set Point CNX Accuracy Precision Foci size, comets & satellites Priority or Risk Overlay Incubation (Time) 4 7 days X Overlay Type CMC vs Avicel C Plate & Sample Prep Confluency % C Plate & Sample Prep Passage number Currently at 149 C Plate & Sample Prep Mixing/pipetting Mixing time 5-30 secs X Virus adsorption Time dry (from aspiration o secs N Virus adsorption Sample Addition (Vol) μl X Overlay Concentration % X Signal Development Incubation Time mins C Virus adsorption Incubation (Time) hours X Plate & Sample Prep Plate manufacturer Currently Greiner, cat. No C Virus adsorption Incubation (Temp) 35-38oC C Virus adsorption Agitation Rocking vs Manual X Plate & Sample Prep Plate Age days C Signal Development Incubation Temp 22-27oC N Plate Fixing Wash repeats 2-4 C Plate Fixing Wash agitation 6-10 swirls N Plate & Sample Prep Dilution Series Factor 2 to 5 C Virus adsorption Incubation (CO2 Conc) % C Overlay Incubation (Temp) 36-38oC C Immuno-staining Wash repeats 1 to 3 C Immuno-staining Wash volume 1-3 ml C Immuno-staining Blocking temp 25-40oC C Immuno-staining Blocking Time mins C Immuno-staining Blocking volume 0.5-2mL C Immuno-staining Primary Ab Vol ml C Immuno-staining Primary Ab Conc 1:1000-1:3000 X Immuno-staining Primary Ab incbtn time 1-6 hr X Immuno-staining Secndry Ab Vol ml C Immuno-staining Secndry Ab Conc 1:500-1:2000 C Immuno-staining Secndry Ab incbtn temp ºC C Immuno-staining Secndry Ab incbtn time mins C Signal Development AP Volume 0.3ml-0.5mL C Plate Fixing Methanol fix time mins C Plate & Sample Prep ph C Overlay Incubation (CO2 Conc) 4-6% C Overlay Volume 2-4mL C

23 Overlay Medium Overlay Concentration 7 Inoculum volume Adsorption time Agitation Incubation time Mixing method 23

24 Screening Designs Selected 2 level fractional factorial with CP for curvature Parameters were a mix of Categorical (binary) or Numerical 24

25 H a lf- N o r m a l % P r o b a b ility H a lf- N o r m a l % P r o b a b ility H a lf- N o r m a l % P r o b a b ility H a lf- N o r m a l % P r o b a b ility Serotype 1 Screening data Design-Expert Software Titre Half-Normal Comets Plot Design-Expert Software Half-Normal Plot Error estimates Error estimates Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration D: Incubation time E: Mixing method F: Overlay medium Positive Effects Negative Effects Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration BC D: Incubation time E: Mixing method F: Overlay medium Positive Effects B-Adsorption time Negative Effects C-Overlay concentration D-Incubation time DE D-Incubation time B-Adsorption time BD E-Mixing method DE 50 E-Mixing method Design-Expert Software Log10(Focus size) Standardized Effect Titer Design-Expert Software Half-Normal Satellites Plot Standardized Effect Comets Half-Normal Plot Error estimates Error estimates Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration D: Incubation time E: Mixing method F: Overlay medium Positive Effects Negative Effects Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration F-Overlay medium D: Incubation time E: Mixing method F: Overlay medium D-Incubation time Positive Effects Negative Effects B-Adsorption time BD C-Overlay concentration A-Infection volume Standardized Effect Foci Size Standardized Effect Satellites 25

26 H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y H a lf - N o r m a l % P r o b a b ilit y Serotypes 2, 3 & 4 are Half-Normal Plot Design-Expert Software Titre Half-Normal Plot Design-Expert Software Titre Half-Normal Plot Error estimates Error estimates ion AC D-Incubation time E-Mixing method A-Infection volume F-Overlay medium Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: CF Overlay concentration D: Incubation time E: Mixing method DE F: Overlay medium Positive Effects Negative Effects C-Overlay concentration Titer AC EF E-Mixing method A-Infection volume B-Adsorption time BD D-Incubation time F-Overlay medium C-Overlay concentration Titer Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration D: Incubation time E: Mixing method F: Overlay medium Positive Effects Negative Effects F-Overlay medium E-Mixing method AE A-Infection volume C-Overlay concentration B-Adsorption time BD D-Incubation time Titer are Standardized Effect Half-Normal Plot Design-Expert Software Sqrt(Focus size) Standardized Effect Half-Normal Plot Design-Expert Software Focus size Standardized Effect Half-Normal Plot Error estimates Error estimates tion CF B-Adsorption time A-Infection volume C-Overlay concentration Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time D-Incubation C: Overlay time concentration D: Incubation time E: Mixing method F: Overlay medium Positive Effects F-Overlay medium Negative Effects Size D-Incubation time F-Overlay medium C-Overlay concentration CD Size Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration D: Incubation time E: Mixing method F: Overlay medium Positive Effects Negative Effects B-Adsorption time CF C-Overlay concentration E-Mixing method D-Incubation time F-Overlay medium Size Standardized Effect Standardized Effect Standardized Effect ftware Half-Normal Plot Design-Expert Software Satellites Half-Normal Plot Design-Expert Software Satellites Half-Normal Plot Error estimates Error estimates ation B-Adsorption time A-Infection volume AD BC D-Incubation time C-Overlay concentration Comets Shapiro-Wilk test W-value = p-value = A: Infection volume B: Adsorption time C: Overlay concentration CD D: Incubation time E: Mixing method F: Overlay medium Positive Effects Negative Effects Satellites Shapiro-Wilk test W-value = p-value = A: Infection volume D-Incubation time B: Adsorption time C: Overlay concentration D: Incubation time CD E: Mixing method F: Overlay medium C-Overlay concentration Positive Effects Negative Effects BD F-Overlay medium B-Adsorption time D-Incubation time E-Mixing method A-Infection volume CF C-Overlay concentration Satellites Standardized Effect Standardized Effect Standardized Effect 26

27 IFA Main Effects & Interactions TITER COMETS PARAMETER Adsorption Time Overlay Concentration Adsorp. tme/overly conc. RESULT MAIN EFFECT MAIN EFFECT INTERACTION PARAMETER MIXING METHOD ADSORPTION TIME INCUBATION TIME RESULT MAIN EFFECT MAIN EFFECT MAIN EFFECT FOCI SIZE INCUBATION/MIXING ADSORPTN/INCUBATN INTERACTION INTERACTION PARAMETER ADSORPTION TIME INCUBATION TIME OVERLAY CONCENTRATION ADSORPTION/INCUBATION RESULT MAIN EFFECT MAIN EFFECT MAIN EFFECT INTERACTION SATELLITES PARAMETER RESULT INFECTION VOLUME MAIN EFFECT OVERLAY CONC MAIN EFFECT 27

28 Response Surface Design Results Optimal design - Mix of numerical and categorical 1. Inoculum volume 2. Adsorption time 3. Incubation time 4. Mixing by pipette 5. Agitation Fixed the: Mixing method (pipette) Chose Avicel for overlay 28

29 Optimisation - 3D Models Titer DENVax 1 29

30 Numerical Optimisation within DX8 Set desired Criteria Review Responses 30

31 Optimal with a robust range JMP Profiler 31

32 Assay Control: control the parameters inside boundaries 32

33 Final Set-points All serotypes were reviewed and suitable set points were decided upon: i. Agitation = static ii. Mixing by pipette = 9 cycles iii. Inoculum volume = 500 μl iv. Adsorption time = 1.5 h v. Incubation time = 5 days Range around set-points determined 33

34 Recap - Data Driven Development Scope Screen Optimize Verify QC/TT Transfer to QC to validate on batches & bring into routine use Explore mildest to most forcing conditions Identify few potential key parameters Focus on vital few & narrow ranges Estimate & utilize interactions to move towards optimum conditions Rattle the cage to deliver a design space

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36 Assay Transfer of Monovalent IFA Nested Design to understand Variance sources, Site to Site differences & assay precision:

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38 This information is extremely useful to decide where to power your replication There s no point in replicating elements within an assay that contribute relatively little towards variance

39 Summary Deconstructed Assay & Prioritised 7 parameters for evaluation Performed a screening assay that selected 5 parameters for optimisation Optimised the parameters that allowed set points to be selected for the 4 serotypes Successfully transferred assay between 3 international sites Nested analysis helped understand the variance sources of the assay for replication decisions

40 What Next? Transfer learnings from monovalent assay into the Tetravalent assay for release of drug product Understand and optimise cell preparation for both assays Design space data will be used for robustness studies in assay Perform validation further Nested analysis to understand vial to vial variation relative to other Usesources data to decide replication regime and to set acceptance criteria for assay validation for imending phase III 40

41 Acknowledgments Dr. Paul Nelson Prism TC Ltd Mr. Stuart Wilson Prism TC Ltd. 41

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