BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Telerik Inc.//Sitefinity CMS 15.4//EN BEGIN:VTIMEZONE TZID:W. Europe Standard Time BEGIN:STANDARD DTSTART:20251002T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=3;BYMINUTE=0;BYMONTH=10 TZNAME:W. Europe Standard Time TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:20250301T020000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYHOUR=2;BYMINUTE=0;BYMONTH=3 TZNAME:W. Europe Daylight Time TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:Date: 24th June 2019\nLocation: Bath University\, 10-4pm UK tim e \;\n\nAgenda:\n\n\n \n \n  \;Time  \;&n bsp\;\n  \;Topic\n \n \n  \;09 :30 -10:00\n Registration\n \n \n &nbs p\;10:00-10:15\n Welcome and Introduction to PSI Scientific Com mittee &\; South West Events\n \n \n \n  \;10:15 -12:00\n Group sequential and adaptive clinic al trial designs \n \n Professor Chris Jennison (Uni versity of Bath)\n \n \n  \;12:00 -12:45\n Lunch\n \n \n  \;12:45 -13:30\n  \;Facilitating Personalised Healthcare With Adaptive Designs \ n \n Chris Harbron\, Senior Principal Statistical Sc ientist\, Roche\n \n \n  \;13:30 -14:15\n Introducing the Adaptive designs CONSORT Extension (ACE) Statement to improve reporting of randomised trials that use an adaptive design \n \n Munya Dimairo (ACE Steering Committee\, Universit y of Sheffield)\n \n \n \n  \;14:1 5- 14:30\n  \;Break\n \n \n  \ ;14:30 -15:15\n Monitoring Outcomes in Adaptive Designs \n \n Sharon Barton\, Associate Director Oncology &\; Ea rly Clinical Development\, AstraZeneca \n \n \n & nbsp\;15:15 -16:00 \;\n A regulatory perspective of adaptiv e design trials \n \n Beatrice Panico\, Senior Medic al Assessor\, (MHRA)\n \n \n  \;16:00 -16:15\ n  \;Close\n \n \n\n\nPresenters: Chris Jennison (University of Bath)\, Munya Dimairo (University of Sheffield)\, Beatrice Panico (MHRA)\, Chris Harbron (Roche)\, Sharon Barton (Astrazeneca) \; \nAdaptive designs are clinical trials that allow for prospectively planne d modifications to one or more aspects of the design based on accumulating data from subjects in the trial and can provide a number of advantages ov er non-adaptive designs. \; During this meeting we will hear about ada ptive sample allocation for phase II/III designs\, a new CONSORT extension reporting guideline for adaptive designs\, regulatory aspects and case st udies.\n\n\n \n \n \n \n \n \n \n \n Chris Jennison (Universi ty of Bath)\,\n Christopher Jennison is Professor of Statistics at the University of Bath\, UK. His PhD research at Cornell University co ncerned the sequential analysis of clinical trials and he has continued to work in this area for the past 35 years. His book with Professor Bruce Tu rnbull\, "Group Sequential Methods with Applications to Clinical Trials"\, is a standard text on this topic and is widely used by practising statist icians. More recently\, he has written with a variety of co-authors on ada ptive trial design and over-arching optimisation of the drug development p rocess.\n Professor Jennison's research is informed by experien ce of clinical trial analysis at the Dana Farber Cancer Institute\, Boston and a broad range of consultancy with Medical Research institutes and Pha rmaceutical companies.\n \n Group sequential and ada ptive clinical trial designs\n We shall describe group sequent ial methods for monitoring a clinical trial that compares a new treatment against a control. This methodology is applicable across a range of respon se distributions. When the primary endpoint is a time-to-event outcome\, t ests constructed using the error spending approach are able to accommodate the unpredictable numbers of events at each analysis. We shall see how gr oup sequential testing can lead to an earlier conclusion of the trial and fewer patients recruited.\n In some Phase III clinical trials\, more than one new treatment is compared to the control. We shall consider an adaptive clinical trial in which two versions of a new treatment are t o be compared with a control when the primary endpoint is overall survival . At an interim analysis\, one of the two treatments will be selected base d on observed progression free survival. Then\, in the remainder of the tr ial new patients will be randomised between the selected treatment and the control.\n This three arm trial requires an adaptive design. A key element of such a design is a closed testing procedure which protects the familywise type I error rate when two different null hypotheses may b e tested. Another crucial component of the design is a combination test th at can merge data from before and after the interim analysis. We shall dis cuss closed testing procedures and combination tests in general before app lying these methods to our three arm trial. With this methodology in place \, we then assess the potential benefits of treatment selection in this ad aptive trial design.\n \n \n \n \n Munya Dimairo (University of Sheffield)\n Munya is a Re search Fellow in Medical Statistics within the Sheffield Clinical Trials R esearch Unit at the University of Sheffield. He is involved in the design\ , conduct\, analysis\, and reporting of clinical trials. He is the lead Tr ial Statistician of an ongoing adaptive multi-arm multi-stage adaptive tri al and IDMC Statistician on several trials. Munya is interested in the use of innovative trial designs and is collaborating on a number of initiativ es to bridge gaps in the practical application of adaptive designs. For ex ample\, he is leading the development of the CONSORT Extension for randomi sed adaptive trials and the creation of an online platform to educate rese archers across disciplines on the practical application of adaptive design s in randomised trials.\n \n Introducing the Adaptiv e designs CONSORT Extension (ACE) Statement to improve reporting of random ised trials that use an adaptive design\n Munya Dimairo on beha lf of the ACE Steering Committee (m.dimairo@sheffield.ac.uk\; mdimairo@gma il.com)\n ACE Steering Committee: Munya Dimairo\; Philip Pallma nn\; James Wason\; Susan Todd\; Thomas Jaki\; Steven A. Julious\; Adrian P . Mander\; Christopher J. Weir\; Franz Koenig\; Marc K. Walton\; Jon P. Ni choll\; Elizabeth Coates\; Katie Biggs\; Toshimitsu Hamasaki\; Michael A. Proschan\; John A. Scott\; Yuki Ando\; Daniel Hind\; and Douglas G. Altman \n The reporting of adaptive designs (ADs) in randomised trials is inconsistent and needs improving 1&ndash\;4. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transpa rency and adequate reporting will enable the potential benefits of ADs to be realised.\n We developed an Adaptive designs CONSORT Extensi on (ACE) guideline through a two-stage Delphi process with input from mult idisciplinary key stakeholders in clinical trials research in the public a nd private sectors from 21 countries\, followed by a consensus meeting 1. Delphi survey response rates were 94/143 (66%)\, 114/156 (73%)\, and 79/14 3 (55%) in round one\, two and across both rounds\, respectively. Members of the CONSORT Group were involved during the development process.\n This talk will summarise the development process and introduce the A CE reporting guideline focusing on new and modified reporting items. The A CE checklist is comprised of seven new items\, nine modified items\, six u nchanged items for which additional explanatory text clarifies further con siderations for ADs\, and 20 unchanged items not requiring further explana tory text. The ACE abstract checklist has one new item\, one modified item \, one unchanged item with additional explanatory text for ADs\, and 15 un changed items not requiring further explanatory text. \n The in tention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibilit y of their methods\, results and inference. We also hope indirectly to fac ilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.\n References\n 1.  \; \; \; \; \; \; Dimairo M\, Coates E\, Pallman n P\, et al. Development process of a consensus-driven CONSORT extension f or randomised trials using an adaptive design. BMC Med. 2018\;16(1):210.\n 2.  \; \; \; \; \; \; Stevely A\, Dima iro M\, Todd S\, et al. An Investigation of the Shortcomings of the CONSOR T 2010 Statement for the Reporting of Group Sequential Randomised Controll ed Trials: A Methodological Systematic Review. PLoS One. 2015\;10(11):e014 1104.\n 3.  \; \; \; \; \; \; Hatfield I\, Allison A\, Flight L\, Julious SA\, Dimairo M. Adaptive designs undert aken in clinical research: a review of registered clinical trials. Trials. 2016\;17(1):150.\n 4.  \; \; \; \; \;  \; Yang X\, Thompson L\, Chu J\, et al. Adaptive Design Practice at the Ce nter for Devices and Radiological Health (CDRH)\, January 2007 to May 2013 . Ther Innov Regul Sci. 2016\;50(6):710-717.\n \n \n \n \n \n Beatrice Panico (MHRA)\n Maria Beatrice Panico is currently a Senior Medical Assessor in th e Clinical Trials Unit at the Medicines and Healthcare products Regulatory Agency (MHRA).\n She is a medical doctor\, fully qualified in Neurology with a PhD in Neuroscience. She has extensive experience in phar macovigilance in the pharmaceutical industry.\n \n \ n MHRA Presentation abstract \n The MHRA supports in novation and several trials with innovative designs are already ongoing in the UK. Some innovative trials are &lsquo\;adaptive design trials&rsquo\; : modifying the conduct of ongoing trials increases the chance of the tria l formally being a success (i.e. that the null hypothesis can be rejected) . A central tenet of adaptive design protocols is that the adaptations are pre-specified in the protocol and are not made on an ad-hoc basis. Trials have to be safe and scientifically sound. It is therefore crucial that Sp onsors of adaptive design trials provide the regulators with a strong scie ntific rationale why an innovative design is the best solution to address the trial objectives rather than a more traditional approach. The rational e should also discuss how the trial integrity will be maintained despite c ontinuous adaptations.\n Adaptations that can prove challenging in the current regulatory scenarios are addition of new Investigational M edicinal Products\, new trial populations and some seamless Phase 2-3 tria ls.\n Such changes can be introduced via substantial amendments .\n However\, if the proposed changes are so extensive that the y change the nature of the initially approved trial (for example\, they ar e not in line with the original research hypothesis\, they make the data o btained up to the point of the amendment inadmissible or make the sponsor lose control of Type 1 error) then a new clinical trial application would probably be necessary. The decision is always on a case by case both for i nitials and amendments.\n In conclusion:  \;adaptations can be acceptable if safe and scientifically justified. Early engagement with regulators is strongly recommended in order to address potential issues o f concerns. \n \n \n \n  \;Chris H arbron (Roche)\n Personalised HealthCare (PHC)\, targeting ther apies to those patients most likely to benefit is becoming an increasingly key strategy within drug development. However during development a challe nge is that there can be uncertainty on the optimal PHC strategy\, both on the need for a selected population and the exact definition of a subpopul ation\, for example which assay to use to measure a biomarker and with wha t cutoff. Adaptive designs provide an efficient way of mitigating this unc ertainty whilst still maintaining the overall rigour and operating charact eristics of the trial. \; I will review several published adaptive des igns for biomarkers and describe in more detail a method for adapting a bi omarker threshold at interim analyses to balance the power of the study an d the precision in estimating the threshold. \n \n \n  \;Sharon Barton (Astrazeneca) \;\n Abstract: With in early clinical trials we aim to make robust decisions as early as possi ble\, typically at a planned interim or final analysis using pre-defined d ecision criteria. \; An alternative approach would be to include conti nuous monitoring on a key efficacy or safety endpoint in addition to these planned analyses. \; This approach uses a predictive power calculatio n to assess the chance of observing a given rate or better. \; The pre dictive power can be recalculated after each patient&rsquo\;s outcome is a vailable and if the predictive power falls below a pre-agreed value then t he arm/study may be stopped. \; Simulation methods are used to evaluat e the operating characteristics of the design and a monitoring plan is cre ated detailing the decision rule after each patient. \; An example wil l be shared outlining how this is planned to be incorporated into a trial using discontinuation rate due to adverse events in the first 4 weeks\, bu t the approach can equally apply to efficacy endpoints. \; Using conti nuous monitoring within a trial may result in quicker decisions that still have robust statistical characteristics. \;\n \n Short bio: Sharon Barton is an Associate Director\, Statistics Team Lead er within Oncology Biometrics at AstraZeneca in Cambridge\, UK. \; She joined AstraZeneca in 2017 and currently leads a team of statisticians su pporting early clinical development. \; Prior to joining AstraZeneca\, Sharon worked at GlaxoSmithKline for 14 years within both early and late phase clinical development across a broad range of disease areas. \; P rior to joining GlaxoSmithKline\, Sharon worked as a statistician for the contract research organisation PPD. \; \n \n \n \ n\n\nRegistration is now closed. \;\n DTEND:20190624T140000Z DTSTAMP:20260913T044720Z DTSTART:20190624T080000Z LOCATION: SEQUENCE:0 SUMMARY:PSI One day Scientific meeting\, South West: Designing and Analysin g Adaptive Trial Design Studies UID:RFCALITEM639248716406046223 X-ALT-DESC;FMTTYPE=text/html:

Date: 24th June 2019

\n

Location: Bath University\, 10-4pm UK time& nbsp\;
\n
\nAgenda:
\n

\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n < /tr>\n \n
 \;Time  \; \; \;Topic
 \;09:30 -10:00Registration
 \;10:00-10:15Welcome and Introduction to PSI Scientific Committee &\ ; South West Events
\n
 \;10:15 -12:00Group sequential and adaptive clinical trial desi gns
\n
\n Professor Chris Jennison ( University of Bath)
 \;12:00 -12:45Lunch
&nbs p\;12:45 -13:30 \;Facilitating Personalised Healthcare With Adaptive Designs
\n
\n Chris Harbron\, Senior Principal Sta tistical Scientist\, Roche
 \;13:30 -14:15Introducing the Adaptive designs CONSORT Extension (ACE) Statement to improve reporting of randomised trials that use an adaptive design
\n
\n

Munya Dimairo (ACE Steering Committee\, U niversity of Sheffield)

\n
 \;14:15- 14:30 \;Break
 \;14:30 -15:15Monitoring Outcomes in Adaptive Designs
\n
\n Sharon Barton\, Associate Directo r Oncology &\; Early Clinical Development\, AstraZeneca
 \;15:15 -16:00 \;A regulatory pers pective of adaptive design trials
\n
\n Beatrice Panico\, Senior Medical Assessor\, (MHRA)
 \;16:00 -16:15 \;Close
\n


\nPresenters: Chri s Jennison (University of Bath)\, Munya Dimairo (University of Sheffield)\ , Beatrice Panico (MHRA)\, Chris Harbron (Roche)\, Sharon Barton (Astrazen eca) \;

\nAdaptive designs are clinical trials that allow for prosp ectively planned modifications to one or more aspects of the design based on accumulating data from subjects in the trial and can provide a number o f advantages over non-adaptive designs. \; During this meeting we will hear about adaptive sample allocation for phase II/III designs\, a new CO NSORT extension reporting guideline for adaptive designs\, regulatory aspe cts and case studies.
\n\n\n \n \n \n \n \n \n \n \n \n \n \ n \n \n \ n \n \n \n \n \n < td>Abstract: Within early clinical trials we aim to make robust decisions as early as possible\, typically at a planned interim or final analysis using pre-defined decision criteria. \; An alternative approach would be to include continuous monitoring on a key efficacy or sa fety endpoint in addition to these planned analyses. \; This approach uses a predictive power calculation to assess the chance of observing a gi ven rate or better. \; The predictive power can be recalculated after each patient&rsquo\;s outcome is available and if the predictive power fal ls below a pre-agreed value then the arm/study may be stopped. \; Simu lation methods are used to evaluate the operating characteristics of the d esign and a monitoring plan is created detailing the decision rule after e ach patient. \; An example will be shared outlining how this is planne d to be incorporated into a trial using discontinuation rate due to advers e events in the first 4 weeks\, but the approach can equally apply to effi cacy endpoints. \; Using continuous monitoring within a trial may resu lt in quicker decisions that still have robust statistical characteristics . \;
\n
\n

Short bio: Sharon Barton is an Associate Director\, Statistics Team Leader withi n Oncology Biometrics at AstraZeneca in Cambridge\, UK. \; She joined AstraZeneca in 2017 and currently leads a team of statisticians supporting early clinical development. \; Prior to joining AstraZeneca\, Sharon worked at GlaxoSmithKline for 14 years within both early and late phase cl inical development across a broad range of disease areas. \; Prior to joining GlaxoSmithKline\, Sharon worked as a statistician for the contract research organisation PPD. \;

\n \n \ n \n
Chris Jennis on photo
\n
\n
\n
\n
\n
\n Chris Jenniso n (University of Bath)\,		Christopher Jennison is Pro fessor of Statistics at the University of Bath\, UK. His PhD research at C ornell University concerned the sequential analysis of clinical trials and he has continued to work in this area for the past 35 years. His book wit h Professor Bruce Turnbull\, "Group Sequential Methods with Applications t o Clinical Trials"\, is a standard text on this topic and is widely used b y practising statisticians. More recently\, he has written with a variety of co-authors on adaptive trial design and over-arching optimisation of th e drug development process.\n

Professor Jennison's research is informed by experience of clinical trial analysis at the Dana Farber Ca ncer Institute\, Boston and a broad range of consultancy with Medical Rese arch institutes and Pharmaceutical companies.
\n
\n Group sequential and adaptive clinical trial designs

\n

We shall describe group sequential methods for monitoring a clinical trial that compares a new treatment against a contr ol. This methodology is applicable across a range of response distribution s. When the primary endpoint is a time-to-event outcome\, tests constructe d using the error spending approach are able to accommodate the unpredicta ble numbers of events at each analysis. We shall see how group sequential testing can lead to an earlier conclusion of the trial and fewer patients recruited.

\n

In some Phase III clinical trials\, more th an one new treatment is compared to the control. We shall consider an adap tive clinical trial in which two versions of a new treatment are to be com pared with a control when the primary endpoint is overall survival. At an interim analysis\, one of the two treatments will be selected based on obs erved progression free survival. Then\, in the remainder of the trial new patients will be randomised between the selected treatment and the control .

\n

This three arm trial requires an adaptive design. A key element of such a design is a closed testing procedure which protects the familywise type I error rate when two different null hypotheses may be tested. Another crucial component of the design is a combination test tha t can merge data from before and after the interim analysis. We shall disc uss closed testing procedures and combination tests in general before appl ying these methods to our three arm trial. With this methodology in place\ , we then assess the potential benefits of treatment selection in this ada ptive trial design.

\n
2T5A9074
\n Munya Dimairo (University of Sheffi eld)		Munya is a Research Fellow in Medical Statistic s within the Sheffield Clinical Trials Research Unit at the University of Sheffield. He is involved in the design\, conduct\, analysis\, and reporti ng of clinical trials. He is the lead Trial Statistician of an ongoing ada ptive multi-arm multi-stage adaptive trial and IDMC Statistician on severa l trials. Munya is interested in the use of innovative trial designs and i s collaborating on a number of initiatives to bridge gaps in the practical application of adaptive designs. For example\, he is leading the developm ent of the CONSORT Extension for randomised adaptive trials and the creati on of an online platform to educate researchers across disciplines on the practical application of adaptive designs in randomised trials.
\n
\n

Introducing the Adaptive designs CONSORT Extension (ACE) Statem ent to improve reporting of randomised trials that use an adaptive design< /p>\n

Munya Dimairo on behalf of the AC E Steering Committee (m.dimairo@sheffield.ac.uk\; mdimairo@gmail.com)

\n

ACE Steering Committee: Munya Dimairo\; Philip Pallmann\; James Wason\; Susan Todd\; Thomas Jaki\; Steven A. Julio us\; Adrian P. Mander\; Christopher J. Weir\; Franz Koenig\; Marc K. Walto n\; Jon P. Nicholl\; Elizabeth Coates\; Katie Biggs\; Toshimitsu Hamasaki\ ; Michael A. Proschan\; John A. Scott\; Yuki Ando\; Daniel Hind\; and Doug las G. Altman

\n

The reporting of adaptive designs ( ADs) in randomised trials is inconsistent and needs improving 1&ndash \;4. Incompletely reported AD randomised trials are difficult to rep roduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contribut es to research waste. Better transparency and adequate reporting will enab le the potential benefits of ADs to be realised.

\n

We de veloped an Adaptive designs CONSORT Extension (ACE) guideline through a tw o-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 coun tries\, followed by a consensus meeting 1. Delphi survey respon se rates were 94/143 (66%)\, 114/156 (73%)\, and 79/143 (55%) in round one \, two and across both rounds\, respectively. Members of the CONSORT Group were involved during the development process.

\n

This ta lk will summarise the development process and introduce the ACE reporting guideline focusing on new and modified reporting items. The ACE checklist is comprised of seven new items\, nine modified items\, six unchanged item s for which additional explanatory text clarifies further considerations f or ADs\, and 20 unchanged items not requiring further explanatory text. Th e ACE abstract checklist has one new item\, one modified item\, one unchan ged item with additional explanatory text for ADs\, and 15 unchanged items not requiring further explanatory text.

\n

The intentio n is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of t heir methods\, results and inference. We also hope indirectly to facilitat e the much-needed knowledge transfer of innovative trial designs to maximi se their potential benefits.

\n

References

\n

1.  \; \; \; \; \; \; Dimai ro M\, Coates E\, Pallmann P\, et al. Development process of a consensus-d riven CONSORT extension for randomised trials using an adaptive design. BMC Med. 2018\;16(1):210.

\n

2.  \; \;&nbs p\; \; \; \; Stevely A\, Dimairo M\, Todd S\, et al. An Invest igation of the Shortcomings of the CONSORT 2010 Statement for the Reportin g of Group Sequential Randomised Controlled Trials: A Methodological Syste matic Review. PLoS One. 2015\;10(11):e0141104.

\n < p>3.  \; \; \; \; \; \; Hatfield I\, Allison A\, F light L\, Julious SA\, Dimairo M. Adaptive designs undertaken in clinical research: a review of registered clinical trials. Trials. 2016\;1 7(1):150.

\n

4.  \; \; \; \; \; \ ; Yang X\, Thompson L\, Chu J\, et al. Adaptive Design Practice at the Cen ter for Devices and Radiological Health (CDRH)\, January 2007 to May 2013. Ther Innov Regul Sci. 2016\;50(6):710-717.

\n
MBeatrice Panico
\n
\n Beatrice Panico (MHRA)		Maria Beatrice Panico is currently a Senior Medical Asses sor in the Clinical Trials Unit at the Medicines and Healthcare products R egulatory Agency (MHRA).\n

She is a medical doctor\, fully q ualified in Neurology with a PhD in Neuroscience. She has extensive experi ence in pharmacovigilance in the pharmaceutical industry.
\n
\n

\n

MHRA Presentation abst ract

\n

The MHRA supports innovation and severa l trials with innovative designs are already ongoing in the UK. Some innov ative trials are &lsquo\;adaptive design trials&rsquo\;: modifying the con duct of ongoing trials increases the chance of the trial formally being a success (i.e. that the null hypothesis can be rejected). A central tenet o f adaptive design protocols is that the adaptations are pre-specified in t he protocol and are not made on an ad-hoc basis. Trials have to be safe an d scientifically sound. It is therefore crucial that Sponsors of adaptive design trials provide the regulators with a strong scientific rationale wh y an innovative design is the best solution to address the trial objective s rather than a more traditional approach. The rationale should also discu ss how the trial integrity will be maintained despite continuous adaptatio ns.

\n

Adaptations that can prove challenging in the curr ent regulatory scenarios are addition of new Investigational Medicinal Pro ducts\, new trial populations and some seamless Phase 2-3 trials.

\n

Such changes can be introduced via substantial amendments.

\n

However\, if the proposed changes are so extensive that t hey change the nature of the initially approved trial (for example\, they are not in line with the original research hypothesis\, they make the data obtained up to the point of the amendment inadmissible or make the sponso r lose control of Type 1 error) then a new clinical trial application woul d probably be necessary. The decision is always on a case by case both for initials and amendments.

\n

In conclusion:  \;adapta tions can be acceptable if safe and scientifically justified. Early engage ment with regulators is strongly recommended in order to address potential issues of concerns.

\n
 \;C hris Harbron (Roche)Personalised HealthCare (PHC)\, targeting therapies to those patients most likely to benefit is becoming an increasingly key strategy within drug development. However during devel opment a challenge is that there can be uncertainty on the optimal PHC str ategy\, both on the need for a selected population and the exact definitio n of a subpopulation\, for example which assay to use to measure a biomark er and with what cutoff. Adaptive designs provide an efficient way of miti gating this uncertainty whilst still maintaining the overall rigour and op erating characteristics of the trial. \; I will review several publish ed adaptive designs for biomarkers and describe in more detail a method fo r adapting a biomarker threshold at interim analyses to balance the power of the study and the precision in estimating the threshold.
 \;Sharon Barton (Astrazeneca) \;
\n
\nRegistration is now closed. \ ;
\n
END:VEVENT END:VCALENDAR