Services for clinical development
Statistics from protocol to reporting
Arlenda can help you in the different stages of a clinical study with all the quality and expertise required by GCP:
- Writing of the protocol, the statistical analysis plan and the clinical study report.
- Programming of your Tables/Figures/Listings in SAS with full QC
- Validation of your SAS programs
Model-based drug development
Model-based Drug Development is becoming the standard to move from pre-clinical to population of patients. It allows:
- better data analysis by making a more effective use of all the available data, resulting in increased knowledge and science-based decision making
- better trial design by understanding the data needed from the future trials and by knowing how best to obtain it to inform future decisions.
Arlenda may provide advices in global mode-based development strategy but also in its concrete implementation.
Translational sciences
Have you ever thought at the impact that the coefficient of variation of the analytical assay, its lower limit of quantification, the acceptance limits put at the laboratory stages, may have on the sample size needed for your clinical studies or even more on the decision taken on the basis of your clinical study results?
This is what Arlenda calls : "connecting the dots", i.e. making the links between the information you have in the laboratories and results of clinical , stability, ... studies. The gain in integrating the information from the laboratory into your statistical analyses may be huge. Arlenda offers you the possibility to make saving by optimal use of all the information you have in hands, for free !
Clinical trial simulations
Everything is said in the "Guidance for Industry, End-of-Phase IIa meeting" from FDA :
"FDA recognizes trial planning may be improved by clinical trial simulations that employ quantitative models of drug-exposure-response, effects in placebo group, and disease progression. FDA would like to encourage the best use of this science to facilitate the exploration of trial design alternatives to increase the likelihood for successful trials."
Arlenda has a large experience in clinical trial simulations and may provide you advices and/or programming codes in SAS, R, WinBUGS,... to help you to design your studies by appropriate modeling of dose-response curves.
Clinical trial predictions
In early development, prediction is key since the purposes are to identify the range of dose, if any, that will guarantee both efficacy and safety in future late phase trials and to minimize the risks of investing in low success but costly late phase trials.
Arlenda has developed several tools including prediction-based clinical utility index (p-CUI) to allow better go/no go decision making. This p-CUI quantifies factors like a product's efficacy, safety, cost and makes trade-offs transparent to decision makers. Arlenda may adapt this tool to your situation.
Bayesian methodology is well suited for making prediction since it allows "to quantify what is going to happen in a trial from any point on (including from the start of the trial), given the currently available results", [D.Berry, 2006 ].
Adaptive and optimal designs
Do you plan to use an adaptive design for your next study? Don't neglect the simulations needed upfront to make sure that you will take the right decision at interim. This is certainly not an easy task and simulations should be performed in a lot of different scenarios to ensure that your decision criteria is robust, whatever will happened in your study.
Arlenda has already been involved in different types of adaptive designs:
- Adapt doses or sample size
- Based on AEs counting or exposure/PK-PD predictions
Arlenda can also propose you Bayesian adaptive sampling time design for constrained PK-PD studies such as pediatric studies for instance.
Arlenda may offer you advices in the setting of your adaptive design, run the simulations or act as independent statistician to conduct the interim analysis.