Vladimir Anisimov | Amgen, Inc (original) (raw)
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Papers by Vladimir Anisimov
arXiv (Cornell University), Dec 25, 2022
Design and forecasting of patient enrollment is among the greatest challenges that the clinical r... more Design and forecasting of patient enrollment is among the greatest challenges that the clinical research enterprize faces today, as inefficient enrollment can be a major cause of drug development delays. Therefore, the development of the innovative statistical and artificial intelligence technologies for improving the efficiency of clinical trials operation are of the imperative need. This paper is describing further developments in the innovative statistical methodology for modeling and forecasting patient enrollment. The underlying technique uses a Poisson-gamma enrollment model developed by Anisimov & Fedorov in the previous publications and is extended here to analytic modeling of the enrollment on country/region level. A new analytic technique based on the approximation of the enrollment process in country/region by a Poisson-gamma process with aggregated parameters is developed. Another innovative direction is the development of the analytic technique for modeling the enrollment under some restrictions (enrollment caps in countries). Some discussion on using historic trials for better prediction of the enrollment in the new trials is provided. These results are used for solving the problem of optimal trial cost-efficient enrollment design: find an optimal allocation of sites/countries that minimizes the global trial cost given that the probability to reach an enrollment target in time is no less than some prescribed probability. Different techniques to find an optimal solution for high dimensional optimization problem for the cases of unrestricted and restricted enrollment and for a small and a large number of countries are discussed.
Pharmaceutical statistics, Jan 3, 2016
Modelling and simulation has been used in many ways when developing new treatments. To be useful ... more Modelling and simulation has been used in many ways when developing new treatments. To be useful and credible, it is generally agreed that modelling and simulation should be undertaken according to some kind of best practice. A number of authors have suggested elements required for best practice in modelling and simulation. Elements that have been suggested include the pre-specification of goals, assumptions, methods, and outputs. However, a project that involves modelling and simulation could be simple or complex and could be of relatively low or high importance to the project. It has been argued that the level of detail and the strictness of pre-specification should be allowed to vary, depending on the complexity and importance of the project. This best practice document does not prescribe how to develop a statistical model. Rather, it describes the elements required for the specification of a project and requires that the practitioner justify in the specification the omission of ...
Statistics in Medicine, 2016
Randomisation schemes are rules that assign patients to treatments in a clinical trial. Many of t... more Randomisation schemes are rules that assign patients to treatments in a clinical trial. Many of these schemes have the common aim of maintaining balance in the numbers of patients across treatment groups. The properties of imbalance that have been investigated in the literature are based on two treatment groups. In this paper, their properties for K > 2 treatments are studied for two randomisation schemes: centre‐stratified permuted‐block and complete randomisation. For both randomisation schemes, analytical approaches are investigated assuming that the patient recruitment process follows a Poisson–gamma model. When the number of centres involved in a trial is large, the imbalance for both schemes is approximated by a multivariate normal distribution. The accuracy of the approximations is assessed by simulation. A test for treatment differences is also considered for normal responses, and numerical values for its power are presented for centre‐stratified permuted‐block randomisat...
Management Systems in Production Engineering, 2019
Polyurethanes are materials usable in wide spectrum of applications. This article is aimed at the... more Polyurethanes are materials usable in wide spectrum of applications. This article is aimed at the properties tailoring of selected polymers by an alteration in initial materials. To achieve that goal, we proposed form the polyurethane matrix by mixing materials that have a different ratio of the initial components. Mathematical model has been developed that describes relationship of structure and strength, deformation, rheological and tribotechnical characteristics of linear block-polyurethanes based on oligoether blends. Oligoethers blend samples were obtained by injection moulding on an automatic thermoplastication machine with varying proportions of the starting components over the whole concentration range. A significant change of properties over the whole concentration range was observed and compositions with unique combination of characteristics have been determined. Obtained dependencies allow to predict the composition of the binary mixture with a tailored level of strength,...
Averaging principle and diffusion approximation for SP
We consider event-driven clinical trials, where the analysis is performed once a pre-determined n... more We consider event-driven clinical trials, where the analysis is performed once a pre-determined number of clinical events has been reached. For example, these events could be progression in oncology or a stroke in cardiovascular trials. At the interim stage, one of the main tasks is predicting the number of events over time and the time to reach specific milestones, where we need to account for events that may occur not only in patients already recruited and are followed-up but also in patients yet to be recruited. Therefore, in such trials we need to model patient recruitment and event counts together. In the paper we develop a new analytic approach which accounts for the opportunity of patients to be cured, as well as for them to dropout and be lost to follow-up. Recruitment is modelled using a Poisson-gamma model developed in previous publications. When considering the occurrence of events, we assume that the time to the main event and the time to dropout are independent random v...
Switching Processes in Queueing Models, Jan 26, 2010
Communications in Statistics - Simulation and Computation, 2014
ABSTRACT An analytic methodology for patient enrolment modelling using a Poisson-gamma model is d... more ABSTRACT An analytic methodology for patient enrolment modelling using a Poisson-gamma model is developed in (Anisimov & Fedorov, 2007). For modelling hierarchic processes associated with enrolment a new methodology using evolving stochastic processes is proposed. This provides rather general and unified framework to describe various operational processes associated with enrolment. The technique for calculating predictive distributions, mean and credibility bounds for evolving processes is developed. Some applications to modelling operational characteristics in clinical trials are considered with focus to modelling events associated with incoming and follow-up patients in different settings. For these models predictive characteristics are derived in a closed form.
Statistics in Medicine, 2010
Some general points regarding efficiency in clinical trials are made. Reasons as to why fitting m... more Some general points regarding efficiency in clinical trials are made. Reasons as to why fitting many covariates to adjust the estimate of the treatment effect may be less problematic than commonly supposed are given. Two methods of dynamic allocation of patients based on covariates, minimization and Atkinson's approach, are compared and contrasted for the particular case where all covariates are binary. The results of Monte Carlo simulations are also presented. It is concluded that in the cases considered, Atkinson's approach is slightly more efficient than minimization although the difference is unlikely to be very important in practice. Both are more efficient than simple randomization, although it is concluded that fitting covariates may make a more valuable and instructive contribution to inferences about treatment effects than only balancing them.
ABSTRACT. Fedorov et al. (2002) gave formulae for the variance of the estimated ECRT (expected co... more ABSTRACT. Fedorov et al. (2002) gave formulae for the variance of the estimated ECRT (expected combined response to treatment) and the optimal number of centres and total number of patients to use in a multicentre trial in a setting where the number of patients on each treatment arm in each centre was considered fixed. Here we extend these results to the setting where enrolment at each centre is considered random. We show that such randomness inflates the size of the variance of the estimated ECRT and give formulae for amount,of inflation. We also show that this inflation factor is increased if the enrolment rates vary over the centres. The time to complete enrolment is a crucial component in the problem of optimal study design. We con-
Contemporary clinical trials, 2016
Designing an oncology clinical program is more challenging than designing a single study. The sta... more Designing an oncology clinical program is more challenging than designing a single study. The standard approaches have been proven to be not very successful during the last decade; the failure rate of Phase 2 and Phase 3 trials in oncology remains high. Improving a development strategy by applying innovative statistical methods is one of the major objectives of a drug development process. The oncology sub-team on Adaptive Program under the Drug Information Association Adaptive Design Scientific Working Group (DIA ADSWG) evaluated hypothetical oncology programs with two competing treatments and published the work in the Therapeutic Innovation and Regulatory Science journal in January, 2014. Five oncology development programs based on different Phase 2 designs, including adaptive designs, and a standard two parallel arm Phase 3 design were simulated and compared in terms of the probability of clinical program success and expected Net Present Value (eNPV). In this article we consider e...
Statistics in medicine, Jan 12, 2017
At the design of clinical trial operation, a question of a paramount interest is how long it take... more At the design of clinical trial operation, a question of a paramount interest is how long it takes to recruit a given number of patients. Modelling the recruitment dynamics is the necessary step to answer this question. Poisson-gamma model provides very convenient, flexible and realistic approach. This model allows predicting the trial duration using data collected at an interim time with very good accuracy. A natural question arises: how to evaluate the parameters of recruitment model before the trial begins? The question is harder to handle as there are no recruitment data available for this trial. However, if there exist similar completed trials, it is appealing to use data from these trials to investigate feasibility of the recruitment process. In this paper, the authors explore the recruitment data of two similar clinical trials (Intergroupe Francais du Myélome 2005 and 2009). It is shown that the natural idea of plugging the historical rates estimated from the completed trial ...
Theory of Probability and Mathematical Statistics
Communications in Statistics: Case Studies, Data Analysis and Applications
Methodology and Computing in Applied Probability
Journal of Biopharmaceutical Statistics, 2017
Designing an oncology clinical program is more challenging than designing a single study. The sta... more Designing an oncology clinical program is more challenging than designing a single study. The standard approaches have been proven to be not very successful during the last decade; the failure rate of Phase 2 and Phase 3 trials in oncology remains high. Improving a development strategy by applying innovative statistical methods is one of the major objectives of a drug development process. The oncology sub-team on Adaptive Program under the Drug Information Association Adaptive Design Scientific Working Group (DIA ADSWG) evaluated hypothetical oncology programs with two competing treatments and published the work in the Therapeutic Innovation and Regulatory Science journal in January, 2014. Five oncology development programs based on different Phase 2 designs, including adaptive designs, and a standard two parallel arm Phase 3 design were simulated and compared in terms of the probability of clinical program success and expected Net Present Value (eNPV). In this article we consider eight Phase2/Phase3 development programs based on selected combinations of five Phase 2 study designs and three Phase 3 study designs. We again used the probability of program success and eNPV to compare simulated programs. For the development strategies we considered, the eNPV showed robust improvement for each successive strategy, with the highest being for a three-arm response adaptive randomization design in Phase 2 and a group sequential design with 5 analyses in Phase 3.
arXiv (Cornell University), Dec 25, 2022
Design and forecasting of patient enrollment is among the greatest challenges that the clinical r... more Design and forecasting of patient enrollment is among the greatest challenges that the clinical research enterprize faces today, as inefficient enrollment can be a major cause of drug development delays. Therefore, the development of the innovative statistical and artificial intelligence technologies for improving the efficiency of clinical trials operation are of the imperative need. This paper is describing further developments in the innovative statistical methodology for modeling and forecasting patient enrollment. The underlying technique uses a Poisson-gamma enrollment model developed by Anisimov & Fedorov in the previous publications and is extended here to analytic modeling of the enrollment on country/region level. A new analytic technique based on the approximation of the enrollment process in country/region by a Poisson-gamma process with aggregated parameters is developed. Another innovative direction is the development of the analytic technique for modeling the enrollment under some restrictions (enrollment caps in countries). Some discussion on using historic trials for better prediction of the enrollment in the new trials is provided. These results are used for solving the problem of optimal trial cost-efficient enrollment design: find an optimal allocation of sites/countries that minimizes the global trial cost given that the probability to reach an enrollment target in time is no less than some prescribed probability. Different techniques to find an optimal solution for high dimensional optimization problem for the cases of unrestricted and restricted enrollment and for a small and a large number of countries are discussed.
Pharmaceutical statistics, Jan 3, 2016
Modelling and simulation has been used in many ways when developing new treatments. To be useful ... more Modelling and simulation has been used in many ways when developing new treatments. To be useful and credible, it is generally agreed that modelling and simulation should be undertaken according to some kind of best practice. A number of authors have suggested elements required for best practice in modelling and simulation. Elements that have been suggested include the pre-specification of goals, assumptions, methods, and outputs. However, a project that involves modelling and simulation could be simple or complex and could be of relatively low or high importance to the project. It has been argued that the level of detail and the strictness of pre-specification should be allowed to vary, depending on the complexity and importance of the project. This best practice document does not prescribe how to develop a statistical model. Rather, it describes the elements required for the specification of a project and requires that the practitioner justify in the specification the omission of ...
Statistics in Medicine, 2016
Randomisation schemes are rules that assign patients to treatments in a clinical trial. Many of t... more Randomisation schemes are rules that assign patients to treatments in a clinical trial. Many of these schemes have the common aim of maintaining balance in the numbers of patients across treatment groups. The properties of imbalance that have been investigated in the literature are based on two treatment groups. In this paper, their properties for K > 2 treatments are studied for two randomisation schemes: centre‐stratified permuted‐block and complete randomisation. For both randomisation schemes, analytical approaches are investigated assuming that the patient recruitment process follows a Poisson–gamma model. When the number of centres involved in a trial is large, the imbalance for both schemes is approximated by a multivariate normal distribution. The accuracy of the approximations is assessed by simulation. A test for treatment differences is also considered for normal responses, and numerical values for its power are presented for centre‐stratified permuted‐block randomisat...
Management Systems in Production Engineering, 2019
Polyurethanes are materials usable in wide spectrum of applications. This article is aimed at the... more Polyurethanes are materials usable in wide spectrum of applications. This article is aimed at the properties tailoring of selected polymers by an alteration in initial materials. To achieve that goal, we proposed form the polyurethane matrix by mixing materials that have a different ratio of the initial components. Mathematical model has been developed that describes relationship of structure and strength, deformation, rheological and tribotechnical characteristics of linear block-polyurethanes based on oligoether blends. Oligoethers blend samples were obtained by injection moulding on an automatic thermoplastication machine with varying proportions of the starting components over the whole concentration range. A significant change of properties over the whole concentration range was observed and compositions with unique combination of characteristics have been determined. Obtained dependencies allow to predict the composition of the binary mixture with a tailored level of strength,...
Averaging principle and diffusion approximation for SP
We consider event-driven clinical trials, where the analysis is performed once a pre-determined n... more We consider event-driven clinical trials, where the analysis is performed once a pre-determined number of clinical events has been reached. For example, these events could be progression in oncology or a stroke in cardiovascular trials. At the interim stage, one of the main tasks is predicting the number of events over time and the time to reach specific milestones, where we need to account for events that may occur not only in patients already recruited and are followed-up but also in patients yet to be recruited. Therefore, in such trials we need to model patient recruitment and event counts together. In the paper we develop a new analytic approach which accounts for the opportunity of patients to be cured, as well as for them to dropout and be lost to follow-up. Recruitment is modelled using a Poisson-gamma model developed in previous publications. When considering the occurrence of events, we assume that the time to the main event and the time to dropout are independent random v...
Switching Processes in Queueing Models, Jan 26, 2010
Communications in Statistics - Simulation and Computation, 2014
ABSTRACT An analytic methodology for patient enrolment modelling using a Poisson-gamma model is d... more ABSTRACT An analytic methodology for patient enrolment modelling using a Poisson-gamma model is developed in (Anisimov & Fedorov, 2007). For modelling hierarchic processes associated with enrolment a new methodology using evolving stochastic processes is proposed. This provides rather general and unified framework to describe various operational processes associated with enrolment. The technique for calculating predictive distributions, mean and credibility bounds for evolving processes is developed. Some applications to modelling operational characteristics in clinical trials are considered with focus to modelling events associated with incoming and follow-up patients in different settings. For these models predictive characteristics are derived in a closed form.
Statistics in Medicine, 2010
Some general points regarding efficiency in clinical trials are made. Reasons as to why fitting m... more Some general points regarding efficiency in clinical trials are made. Reasons as to why fitting many covariates to adjust the estimate of the treatment effect may be less problematic than commonly supposed are given. Two methods of dynamic allocation of patients based on covariates, minimization and Atkinson's approach, are compared and contrasted for the particular case where all covariates are binary. The results of Monte Carlo simulations are also presented. It is concluded that in the cases considered, Atkinson's approach is slightly more efficient than minimization although the difference is unlikely to be very important in practice. Both are more efficient than simple randomization, although it is concluded that fitting covariates may make a more valuable and instructive contribution to inferences about treatment effects than only balancing them.
ABSTRACT. Fedorov et al. (2002) gave formulae for the variance of the estimated ECRT (expected co... more ABSTRACT. Fedorov et al. (2002) gave formulae for the variance of the estimated ECRT (expected combined response to treatment) and the optimal number of centres and total number of patients to use in a multicentre trial in a setting where the number of patients on each treatment arm in each centre was considered fixed. Here we extend these results to the setting where enrolment at each centre is considered random. We show that such randomness inflates the size of the variance of the estimated ECRT and give formulae for amount,of inflation. We also show that this inflation factor is increased if the enrolment rates vary over the centres. The time to complete enrolment is a crucial component in the problem of optimal study design. We con-
Contemporary clinical trials, 2016
Designing an oncology clinical program is more challenging than designing a single study. The sta... more Designing an oncology clinical program is more challenging than designing a single study. The standard approaches have been proven to be not very successful during the last decade; the failure rate of Phase 2 and Phase 3 trials in oncology remains high. Improving a development strategy by applying innovative statistical methods is one of the major objectives of a drug development process. The oncology sub-team on Adaptive Program under the Drug Information Association Adaptive Design Scientific Working Group (DIA ADSWG) evaluated hypothetical oncology programs with two competing treatments and published the work in the Therapeutic Innovation and Regulatory Science journal in January, 2014. Five oncology development programs based on different Phase 2 designs, including adaptive designs, and a standard two parallel arm Phase 3 design were simulated and compared in terms of the probability of clinical program success and expected Net Present Value (eNPV). In this article we consider e...
Statistics in medicine, Jan 12, 2017
At the design of clinical trial operation, a question of a paramount interest is how long it take... more At the design of clinical trial operation, a question of a paramount interest is how long it takes to recruit a given number of patients. Modelling the recruitment dynamics is the necessary step to answer this question. Poisson-gamma model provides very convenient, flexible and realistic approach. This model allows predicting the trial duration using data collected at an interim time with very good accuracy. A natural question arises: how to evaluate the parameters of recruitment model before the trial begins? The question is harder to handle as there are no recruitment data available for this trial. However, if there exist similar completed trials, it is appealing to use data from these trials to investigate feasibility of the recruitment process. In this paper, the authors explore the recruitment data of two similar clinical trials (Intergroupe Francais du Myélome 2005 and 2009). It is shown that the natural idea of plugging the historical rates estimated from the completed trial ...
Theory of Probability and Mathematical Statistics
Communications in Statistics: Case Studies, Data Analysis and Applications
Methodology and Computing in Applied Probability
Journal of Biopharmaceutical Statistics, 2017
Designing an oncology clinical program is more challenging than designing a single study. The sta... more Designing an oncology clinical program is more challenging than designing a single study. The standard approaches have been proven to be not very successful during the last decade; the failure rate of Phase 2 and Phase 3 trials in oncology remains high. Improving a development strategy by applying innovative statistical methods is one of the major objectives of a drug development process. The oncology sub-team on Adaptive Program under the Drug Information Association Adaptive Design Scientific Working Group (DIA ADSWG) evaluated hypothetical oncology programs with two competing treatments and published the work in the Therapeutic Innovation and Regulatory Science journal in January, 2014. Five oncology development programs based on different Phase 2 designs, including adaptive designs, and a standard two parallel arm Phase 3 design were simulated and compared in terms of the probability of clinical program success and expected Net Present Value (eNPV). In this article we consider eight Phase2/Phase3 development programs based on selected combinations of five Phase 2 study designs and three Phase 3 study designs. We again used the probability of program success and eNPV to compare simulated programs. For the development strategies we considered, the eNPV showed robust improvement for each successive strategy, with the highest being for a three-arm response adaptive randomization design in Phase 2 and a group sequential design with 5 analyses in Phase 3.