tom parke [email protected] implementing adaptive clinical trials 4: drug supply
TRANSCRIPT
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Overview
• There are more treatment arms• How do we supply more doses?
• Arms may be dropped / introduced or arms may become more / less likely to be allocated• We don’t know how much of each
dose we will need make / package?• We don’t know which doses to ship?
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1. How to make and supply many treatment arms
2. How much to make?
3. How much to supply?
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More treatment arms
• How to manufacture / deliver multiple treatments?• manufacture each one• use combinations• may need multiple placebos• how to ensure patient compliance?
• How to limit overage from additional treatment packs types?
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How many treatment arms?
• 8 doses is probably enough• Often use less (4-6)• Might use more (but only if it was easy)• Might start with few doses and add ‘in between
doses’ only where needed.
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Examples
• Stroke: 16 doses (IV)• Migraine: 6 doses• Other A: 3 dose combinations• Other B: 5 doses• Other C: 7 doses and 4 doses
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Examples
• IV with 3 concentrations – randomiser sent ‘recipe’ to centre
• Blister pack with all doses (single shot)
• Take a combination • take a blue pill and a red pill
• Make all 4 doses
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Combinations
• Can try to make as few dose strengths as possible ...• Strengths: 0, 1, 3 & 4 – in combinations of 2• Strengths: 0, 1, 9 & 81 – in combinations of 3• Strengths: 12.5, 50, 150 – in combinations of 3
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Combinations cont’d
• But can be difficult to predict required quantity of each strength.
• Possibly simpler is say:• Strengths: 0, 1, 2, 4, 6, ... using the 1 dose to
make intermediate doses. (0,0), (1,0), (2,0), (2,1), (4,0), (4,1), ...
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Combinations
• Assume: • that 20% get placebo, • 20% the best dose, • 15% the next two best doses, • 10% the two after that and • 5% the two after that.
• Consider min & max requirements for tablets for each treatment dose in turn being ‘best’.
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Maximum required tablets per 100 subjects randomized
Scheme 1 Scheme 2
Dose Min Max Min Max
0 55 85 75 90
1 20 65 40 50
2 / 3 35 60 15 35
4 25 75 20 35
6 10 35
Total 285 245
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Result
• Need to make 14% fewer tablets per 100 subjects with simpler – more strengths scheme 2.
• 47% less overrage to supply combinations.
• Your mileage may vary, but fewer tablet strengths may not mean less wastage
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Just in time packaging
• Capsules can easily be made different strengths• If they can be made quickly & to order it is easier:
• to provide adaptive supply as randomisations change• to prepare new doses to add at interim
• Need prior warning from DMC before dropping or adding treatment arms.
• DMC need to know lead time for implementation.• DMC need to monitor accumulating data /
information• predict interim decision• predict timing of decision
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1. How to make and supply many treatment arms
2. How much to make?
3. How much to supply?
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Example Trial
• Phase 2 trial of a Neuropathic Pain compound.
• 8 doses plus placebo
• Taken daily for 6 weeks
• Maximum of 250 subjects
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Example simulation: fitted curve
Fitted response over progressive weeks
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Example simulation: adaptive dose allocation
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How much of each dose?
• How can we determine how much to manufacture / package?
• When should we schedule new batches to be manufactured / packaged?
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Simulate the adaptive trial
• Use not just one scenario, but the range of plausible scenarios
• A max for each treatment arm that covers 90% or 95% of cases should suffice
• Allow more for Placebo• Propose the limit to the designers – allow
them to include the limit in their simulations.
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How many do have to be able to supply?
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Can we reduce the variance
• Look at placebo distribution• P(allocate to placebo) is fairly uniform • Length of whisker is just randomness
of allocation.• Don’t block because ratios are 2 sig fig
(need blocksize of 100) and changed every week.
• How about partial blocking?
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Partial Blocking
Placebo: 25%Dose1: 6%Dose2: 9%Dose3: 15%Dose4: 26%Dose5: 13%Dose6: 6%
1 Placebo1 Dose4+ 2 of:Dose1: 12%Dose2: 18%Dose3: 30%Dose4: 2%Dose5: 26%Dose6: 12%
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Treatment arms dropped or introduced
• Trial may not adapt smoothly but only at interims (1-4 a trial)
• At interim arms may be introduced, or dropped• Explore intermediate doses in area of
interest• Extend range• Drop ineffective doses
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Adding Doses At InterimR
espo
nse
Initial Doses
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Treatment arms dropped or introduced
• Can we reduce manufacturing / packaging and overage for arms that are dropped?
• Can we avoid unnecessary re-supply for expired batches?
• Can we avoid manufacturing / packaging an arm that is not then introduced?
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Randomisation
• Will be central, no site based
• Need to have all possible doses at each center
• Amount of wastage at centres that don’t recruit at all will be all the greater.
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Simulate the supply
• Model:• Centers• Packs• Subjects• Randomization• Shipments• Depots
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Simulate the supply Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
0.78 0.430.080.21
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Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
Simulate the supply
0.66 0.010.970.14
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Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
Simulate the supply
0.23 0.850.400.61
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Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
Simulate the supply
0.08 0.370.780.72
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Simulating adaptive trials Central Pharmacy
Depot 1 Depot 2
Center 1 Center 4 Center 3 Center 2
P(R1)=0.05 P(R4)=0.02 P(R3)=0.04 P(R2)=0.02
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Simulating adaptive trials
• Need to manage pack types
• Need to include the adaptive randomisation – use output of simulation of adaptive trial:
• Run supply simulations with many different randomisations
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Run Simulations before Trial
• Run 1000 simulations of the entire trial, with no supply cap (2 seconds per simulation for example of 20 centers x 400 days)• Get distribution of:
• trial length• number of lost subjects• packs shipped from central pharmacy
• If number subject lost unacceptable, check re-supply parameters & re-simulate
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Chart the results of the simulations
Probability of losing subject
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 1 2 3 4 5 6 7 8 >8
Subjects lost
Pro
bab
ilit
y
Re-supply A
Re-supply B
Re-supply C
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Check Total Required Supply
• Use number of packs shipped from pharmacy to estimate required supply.
• Check over different scenarios that effect pack usage (e.g. adaptive randomisation scenarios)
• Check with simulation• Estimate likely overage from simulations
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Distribution of Required Supply
Number of High Dose Packs shipped over 100 simulations
0
5
10
15
20
25
30
35
370 380 390 400 410 420 430 440 450 460 470
Number of packs
% o
f ti
mes
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Simulate what-if scenarios
• Frequency of re-supply to a patient (pack sizes)
• Adaptive vs non-adaptive
• Manufacture/package all upfront or make and initial stock and subsequent batches
• Effect of batch expiry
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Using the simulations during the study
• Simulate forwards• Do we have enough supply?• Do have supply we can spare to another
study?• When do we need that next batch?• What if we add / remove centres from the
trial?
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Treatment arms dropped or introduced
• Monitor trial data regularly and prime manufacturing / packaging
• Extend treatments by using dose combination – adding 1 dose to 0,2,4,6.
• Manufacture remainder after interim• Use predictive power report to start manufacturing
before interim.
Start of trial
Interim
End of trialManufacturing time
Initial Supply
Final Supply
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Randomisation – Reduce Wastage
• Use site based randomisation first, then central randomisation
• Supply just in time – monitor the presence of subjects in screening
• Pre-randomise subjects during screening and supply only what is needed.
• Monitor and model recruitment rates during the trial and auto adjust the re-supply rules accordingly
• Close non-recruiting centers and re-allocate supply
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1. How to make and supply many treatment arms
2. How much to make?
3. How much to supply?
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Re-supply during the study
• What shipments should be sent today?
• Load current data• recruitment rates• shipments• location of available stock
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Treatment arms become more / less likely to be
allocated• How do we ensure there is enough
stock at centres for arms that are becoming more likely to be allocated?
• How do we ensure that we don’t over supply arms that are less likely to be allocated?
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Adaptive re-supply algorithm
• Re-supply using a Bayesian self-tuning scheme.
• At each centre the stock required is based on: Current stock. Packs in transit to the centre. Subjects likely to be recruited. Recruited subjects requiring fresh
supplies.. Drug in stock which is about to expire
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Adaptive re-supply algorithm (2)
• Calculate for a look ahead time plus the time required to re-supply the centre.
• Use a maximum acceptable probability of subjects being lost on recruitment - supplies are dispatched if that (floor) level will be exceeded.
• Shipment is sized to reduce the probability of loosing a subject to below a lower maximum acceptable probability (ceiling) level.
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Re-supply report
Weeklyreport
Adaptivere-supply
Current supply state
Current % randomizationto different arms
Currentpatientscreeningdata
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The Wyeth Experience: • Working with Adaptive Partner, developed tool to
monitor site inventories:• Tracked treatment inventories at site.• Provided predicted requirements based on 99% and 95%
certainty of randomization revision.• Predictions only based on patients within 4 days of end of
screening period to prevent calculating demand on dropped patients.
• Provided “pick list” of supplies required by site to accommodate the updated codes.
• Information was provided to Clinical Supplies one week prior to having codes loaded into IVRS.
• NO FORCED TREATMENT ALLOCATION occurred in this study!
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And the winner is ... • Additional supplies were manufactured, packaged
and stored at regional warehouses to accommodate evolving supply demands
• Overall cost of drug supply for this study: • Cost of adaptive design: $422,000 • Number of patient kits packaged:1440• Cost of traditional design: $201,000• Number of patient kits packaged: 686
• But, savings to Clinical for closing study 2 months earlier and 180 less patients?
$1.5 million
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Summary
• Adaptive trials are a challenge to supply (but they’re worth it)
• More doses, less certainty
• Use better tools:• simulator• adaptive re-supply• monitoring of patients in screening