Timings: 09:30  17:00 UK
Time
\nLocation: Royal Statistical Society
\nAddress: 12 Errol Street\, London
\nBayesian method s are being increasingly used in the design and analysis of trials through all stages of clinical drug development. This meeting will include talks on two areas of application commonly used in early phase trials &ndash\; d ose selection and biomarkers. The meeting will include a range of case stu dies presented from different therapeutic areas. More details to follow.&n bsp\;
\nRegistration is now closed.
\nAgenda
\n \nTime  
Registration  
\n 09.55  10.00 \n  \n Welcome and Introduction \n 
\n 10.00  10 .40 \n  \n

\n
10.40  11.20  \n

\n
11.20  11.40 \n  \n Break \n < /td>\n 
\n 11.40  12.20 \n  \n A Bayesian informat
ion theoretic design for phase I dose finding trials without monotonicity
assumption 
\n 1 2.20  13.00 \n  \n Bayesian hi
erarchical model for dose escalation 
\n < p>13.00  13.50\n  \
n Lunch \n 
\n 13.50  14.30 \n \n  \n The use of formally elicited
priors to aid the design of a phase 2B dose ranging study 
\n 14.30 15.10 \n  \n Bayesian methods for de
sign and analysis of clinical trials assessing multiple treatments and bio
markers 
\n
15.10  15.30 \n  \n Break \n 
\n 15.30  16.10 \n  \n Error rates control vi
a shrinkage priors in multivariate errorinvariable doseresponse models<
/strong> 
\n
 \n Prior elicitation and translation of
biomarkers to aid clinical development plans and compound selection 
\n 16.50  17.00 \n  \n Close \n 
\n \; \n Rev Thomas Bayes  Bayesian methods are being increasingly used in the design a
nd analysis of trials through all stages of clinical drug development. Thi
s meeting will include talks on two areas of application commonly used in
early phase trials &ndash\; dose selection and biomarkers. The meeting wil
l include a range of case studies presented from different therapeutic are
as. \; \n 
Andy Grieve\, UCB  F
irstinHuman Studies: Practice or Principle \n < br />\n Abstract: \;The last 12 years has seen two FIH s tudies hit the newspaper headlines: the study of TGN1412 conducted at Nort hwick Park Hospital in the UK and the study of BIA 10‐2474 conducted in Re nnes in France. Both studies led to catastrophic outcomes for the voluntee rs involved. As a result of the first study two investigations were establ ished. The first was setup by the MHRA and their final report\, Duff et a l (2006)\, appeared in December 2006. The second was established by the Ro yal Statistical Society(RSS) to look at statistical issues involved in FIH studies. The resulting report\, Senn et al (2007)\, made 21 recommendatio ns\, both practical and methodological. After the second study a subgroup of the RSS working party provide a commentary on statistical issues invol ved\, Bird et al (2017). As a result of the Duff report the Commission for Human Medicines established an Expert Advisory Group (EAG) on Clinical Tr ials in 2007 to review FIH protocols for three types of new compounds. I w as a coauthor on the two statistical reports and served on the EAG. In th is talk I review practical and methodological issues involved in FIH studi es based on my experience serving on these three groups. \n \n Bird SM\, Bailey RA\, Grieve AP\, Senn S. Statistical issues in first ‐in‐human studies on BIA 10‐2474: Neglected comparison of protocol against practice. Pharmaceutical Statistics 2017\;16:1006. \nExpert Scientific Group on Ph ase One Clinical Trials (Final report of a group convened by UK's Medicine s and Healthcare Regulatory Authority and chaired by Professor Sir Gordon Duff)\, Final report online 6 December 2006\, see http://webarchive.nationalarchives.gov.uk/+ /dh.gov .uk/ en/ publicationsandstatistics/ publications/publicationspolicyandguid ance/ dh_063117 (acc. Jan 2018). \nSenn S\, Amin D\, Bailey RA\, Bird SM\, Bogacka B \, Colman P\, Garrett A\, Grieve A\, Lachmann P. Statistical issues in fir st‐in‐man studies. Journal of the Royal Statistical Society: Series A (Sta tistics in Society) 2007\; 170:51779. \n 
\n Model based dose escal ation: in practice \nAbstract: At AstraZenec a\, the implementation of a model based Bayesian dose escalation design in Oncology phase 1 studies has been facilitated by putting practical consid erations in place that address the operational challenges that arise due t o increased statistical complexity that accompanies the methodology. We wi ll discuss a practical case study\, describing the first time that this ap proach was implemented at AstraZeneca\, including the options explored for specifying the prior\, the advantages of the approach together with pract ical and methodological learnings for future studies. \; The extension to 2drug combination dose escalation studies will be introduced.< /p>\n  
A Bayesian information theoretic
design for phase I dose finding trials without monotonicity assumption \n \n \n
Biography: Pave l did his undergraduate studies in the National Research University Higher School of Economics\, Moscow\, Russia. He worked on informationtheoretic aspects in statistics in the International Laboratory of Stochastic Analy sis. Currently\, Pavel is a PhD student in Lancaster University where he w orks on the project &ldquo\;Dose finding for combination trials with many treatments&rdquo\; under supervision of Professor Thomas Jaki. Pavel is a MarieCurie Fellow in the IDEAS network. The aim of his project is to deve lop novel dose finding designs which do not require parametric assumptions and can be applied to various clinical trials. \; \n  
< img src="https://psiweb.org/images/defaultsource/defaultalbum/alessandro matano.jpg?sfvrsn=d30fdfdb_0&\;MaxWidth=150&\;MaxHeight=&\;Scale Up=false&\;Quality=High&\;Method=ResizeFitToAreaArguments&\;Signa ture=4B77C05F84747D6C35DF45A5B9D3737A" datamethod="ResizeFitToAreaArgumen ts" datacustomsizemethodproperties="{'MaxWidth':'150'\,'MaxHeight':''\,'S caleUp':false\,'Quality':'High'}" datadisplaymode="Custom" alt="Alessandr o Matano" title="Alessandro Matano" style="marginleft: 10px\; marginrigh t: 10px\;" />  Bayesian hierarchical model for dos
e escalation \n \n \n Ab
stract: Clinical trials with multiple strata (e.g. indication\, d
ose regimen\, mutation status) are increasingly used in drug development.
In dose escalation trials\, where data are often sparse and a multiple str
ata analysis may be the only option to study a new treatment\, good statis
tical inference and decisionmaking can be challenging. Inferences from si
mple pooling or stratification are known to be inferior to hierarchical mo
deling methods\, which build on exchangeable strata parameters to allow bo
rrowing information across strata. However\, the standard exchangeability
(EX) assumption bears the risk of too much shrinkage and excessive borrowi
ng for extreme strata. This talk will present the exchangeabilitynonexcha
ngeability (EXNEX) approach in dose finding studies\, as a robust extensio
n of the standard EX approach. It allows each stratumspecific parameter t
o be exchangeable with other similar strata parameters or nonexchangeable
with any of them. A case study from a Phase I trial will also be shown. Biography: After the degree in St atistics for biomedicine\, environment and technology from the university of Rome &ldquo\;La Sapienza&rdquo\; (2008)\, Alessandro joined the pharmac eutical industry (Novartis). He is currently working as Associate Director of Biostatistics in the area of Phase I/II Oncology clinical trials in Ea rly Development Biostatistics (EDB) group. Prior to join the EDB Oncology group Alessandro has worked as trainee in the CISMethodology Group\, supp orting the methodological development and implementation of oncology Bayes ian single agent/combination dosefinding study design. \n 
\n \n Doug Thompson\, GSK  The use of formally elicited priors to aid the design of a ph
ase 2B dose ranging study \n \n \n \n Abstract: \;
The use of assurance
to quantify the probability of success of a proposed parallel group clinic
al trial is well understood. This framework extends naturally to studies w
ith other designs\; including when evaluating dose response is the primary
focus. Prior distributions formally elicited about the mean response at c
ertain dose levels can be used to set certain constraints such that a spre
ad of plausible three parameter Emax curves may be generated. In this pre
sentation\, we will discuss our experiences in the development of a dose r
esponse trial simulator. We illustrate how such an approach may be used to
help characterise interim futility rules\, dose adaptation and assurance.
Biography: Doug Thompson has b een at GlaxoSmithKline for over three years working on the design\, analys is and reporting of clinical trials in rare diseases. He studied statistic s at the University of Glasgow as an undergraduate before going on to unde rtake a PhD at the University of Edinburgh on the development of a risk st ratified approach for the treatment of acute stroke patients\, funded thro ugh the MRC Hubs for Trials Methodology Research. \n 
< /span>  Bayesian methods for design and analysis of clinical trial
s assessing multiple treatments and biomarkers \n \n \n Abstract: Response to treatments is often highly heterogeneous\, especially ones that are targeted at speci fic biological pathways. The increasing availability of biomarkers and tar geted treatments has led to the need for trial designs that efficiently te st new treatments in biomarkerstratified patient subgroups. Often new tre atments are targeted at a specific biomarker subgroup\, but may in fact wo rk in a narrower or broader set of patients. \n<
span style="fontsize: 12px\; fontfamily: Arial\;">I will discuss Bayesia
n adaptive methodology for trials that have multiple treatments and biomar
kers. The proposed design incorporates biological hypotheses about the lin
ks between treatments and biomarker subgroups\, but allows alternative lin
ks to be formed during the trial. The statistical properties of the method
compare well to alternative designs available. \; This design has bee
n developed for trials in ovarian cancer and breast cancer and some method
ology issues specific to each application will be discussed. These include
the use of continuous biomarker information to allocate patients and addi
ng in new treatments and biomarkers during the trial. Biography: James Wason is a Professor of Biostatist ics at Newcastle University and a Programme Leader at the MRC Biostatistic s Unit. He leads a research group focused on development of statistical me thods for more efficient trials. His research interests are adaptive desig ns\, using biomarkers prospectively during trials and analysis of composit e endpoints. As well as working on methodology\, James is very interested in applying novel methods in real clinical trials and is currently involve d in several ongoing trials using novel designs. \n < /td>\n 
Fabio R igat\, GSK  Error rates control via shrinkage prio
rs in multivariate errorinvariable doseresponse models \n \n Abstract: When planning & amp\; analysing limited numbers of doseresponse data\, the risk of false positive results may be considerable. In this case\, priors can be used to penalise inferences for doseresponse parameters so as to reduce this ris k. We demonstrate a simple example of such priors for analysing the multiv ariate relation between the dose of an investigational asset administered to a cohort of cancer patients and the associated average change in the ex pression of several target genes. This analysis is further robustified by identifying error terms capturing the technical variability of these bioma rker data from those representing sampling variation. \; \n \n 
\n \n Abstract: The talk will show how prior elicitati on of a pharmacodynamic (PD) biomarker can be used to estimate a design pr ior to be used in designing clinical trials. \; In addition\, if the t ranslation of the biomarker to efficacy or safety is elicited\, then this can help evaluate the benefits of the biomarker and how decisions may be m ade based on the biomarker. \; An example will be given where efficacy and safety biomarkers are used to compare several compounds being conside red for the same indication. \; The elicitation of the translation all ows us to weigh up which biomarker is most relevant in making the decision over which compound to progress first. \; When this decision can be m ade\, preclinical\, Phase 1 or Phase 2\, can be compared. \n \n Biography: Trevor has been the Group Lead for Early Phase Neuroscience Statistics at Eli Lilly since Sep tember 2011 covering neurodegeneration\, psychiatric illnesses and pain.&n bsp\; This covers the clinical planning after Candidate Identification thr ough to the decision to proceed to Phase 3. \; Prior to this he was at Pfizer in Kent from 1998\, where he worked on early clinical development as well. \; Much of the work was in pain and many biomarker and method ology studies including: fMRI\, other imaging biomarkers\, healthy volunte er challenge models and patient biomarkers. Trevor has also worked for Bio SS in Scotland and at Rothamsted. \n 
\n
\nPlease register before W
ednesday 21st February 2018. \;
\n
\nPlease contact
the PSI secretariat on psi@mcigroup.com if you
have any dietary requirements or queries about the event.
\n \; \n  \n Registration Fees \n 
\n PSI Member \n  \n £\;40 + VAT \n 
\n NonMember \n  \n £\;13
5 + VAT 
\n Andy Grieve\, UCB Pharma \n 
\n E
rror rates control via shrinkage priors in multivariate errorinvariable
doseresponse models 
\n
Error rates control via shrinkage priors in multivari
ate errorinvariable doseresponse models 