SPEED MATTERS, QUALITY MATTERS
Shaping The Future Of Drug Development
U-Design is a Software-as-a-Service biostatistics platform that delivers innovative optimized statistical designs to improve the efficiency, speed, and safety of drug development
The only SaaS platform enabling head-to-head comparison of different innovative adaptive designs on demand.
Ready generation of enterprise-grade protocol templates that have statistical sections filled in with simulation results for real-world clinical trials.
The simulation results are reproducible and can be shared with regulatory agencies seamlessly.
FDA conducted a public workshop on March 20th, 2018 to discuss the use of complex innovative designs (CID) in clinical trials of drugs and biological products to inform regulatory decision making.
FDA launched a pilot program in August 2018 for sponsors planning to use innovative trial designs that would provide substantial evidence of effectiveness.
“The adoption of novel clinical trial designs and methods for analyzing data are a key to advancing innovation in the development of drug and biologics for hard to treat medical conditions”, said former FDA Commissioner Scott Gottlieb, M.D. in August 2018.
Greatly simplifies the adoption of novel designs for dose finding, making it possible to create such designs without programming efforts or even by non-statisticians, all with a few button clicks.
Cost Saving & Patient Safety
More efficient dose finding, enhanced patient safety and significant overall cost savings for phase 1 clinical trial resulted from shortened trial duration and optimized sample size, by readily applying novel designs.
Enables thorough examination and comparison of operating characteristics of different dose finding designs effected by convenient simulations.
Novel designs for dose finding are often based on complex mathematical modeling and algorithms, which are difficult and time-consuming to implement
Currently, the use of novel designs for real-world trials requires ad-hoc computer programs written by advanced statisticians and reviewed by regulatory agents in a case-by-case fashion
HOW IT WORKS
Statistically Reliable Results
It takes a large number of simulations of model based complex designs to generate statistically reliable results, which helps to make sure that clinical and scientific questions can be addressed with high probability
FDA requires computer simulations for complex adaptive and Bayesian designs to determine their operating characteristics
Help these involved to gain clear understanding of a complex design’s operating characteristics and how design choices affect the outcome of the trial
Facilitate communications and provide justification of the design for the study team, regulator and sponsor, etc.
Bayesian Adaptive Designs
Offers a wide selection of best-in-class innovative Bayesian adaptive designs
And many more ...
This is the simplified version of the single-agent cohort-based dose finding designer. Many inputs are preset, such as scenarios and the number of simulations to run. However, it produces and presents results the same way as that for the full version. It is intended as a quick demonstration of how U-Design works.
Single Agent Cohort-Based Designs
An integrated tool supporting the simulation-based comparison among 7 main-stream dose-finding designs. This module provides both the modern Bayesian model-based designs, including the i3+3 design (Liu et al., 2019), the mTPI design (Ji et al., 2010), the mTPI-2 design (Guo et al., 2017), the continual reassessment method (CRM) (O'Quigley et al., 1990), and the Bayesian logistic regression method (BLRM) (Neuenschwander et al., 2008), and the algorithm-based designs, including the 3+3 design and the modified cumulative cohort design (mCCD; the original CCD design was introduced in (Ivanova et al., 2007).
Single Agent Rolling-Based Designs
Targeting the key point of time-consuming clinical trials, the module of Rolling-Based Designs is an innovative tool that allows users to compare how long a trial would take under different designs in real-life enrollment settings. This module includes rolling-based designs (rolling six (Skolnik et al., 2008) and R-TPI (Guo et al., 2019) that aim to accelerate phase 1 trials, and cohort-based designs (3+3 and mTPI-2 (Guo et al., 2017)) in which an additional “decision-in-advance” rule is applied to further mimic the real-life trials. This module for rolling-based designs is the only tool on the market that incorporates the comparison of trial duration among different designs and up to four designs can be compared side-by-side.
Single Agent Decision & MTD
A simple-to-use tool that includes
- Decision Table: The decision tables can be generated for the i3+3, mTPI, mTPI-2, mCCD and 3+3 designs, which can be used to conduct a phase I dose-finding trial. The CRM and BLRM designs do not provide decision tables before the trial is started. However, for these designs we provide empirical decision tables after running simulations.
- MTD Estimation: Based on the Pool Adjacent Violators Algorithm (PAVA), the MTD can be estimated when the trial is completed and data collected.
Why do I need to register?
After registration, you will have created an account on U-Design website. Once logged into your account, you will be able to access all the tools and utilities, such as does-finding designers and decision tables. A complete history of running simulations for dose finding designs will be stored in your account.
Is registration free and how do I register?
Yes, registration is completely free. Please go to the Registration page to register.
Are tools and utilities provided by U-Design free to use?
Yes, you could run up to 10 simulations at one time for a scenario of any design. However, you need to purchase a subscription plan to be able to run more simulations and generate decision tables.
I want to learn more about U-Design. Are there demos or tutorials?
Yes, please go to HOW IT WORKS section for a quick demo and tutorials.
- How do I purchase a subscription?
Can I cancel my subscription?
Yes, you could cancel your subscription at any time. Please go to My Orders, at the top of which you will find your current subscription and then click the "Cancel" button next to it.
I received a notice that my subscription payment failed. What should I do?
By purchasing a subscription plan, your credit card on file will be charged periodically depending on the type of subscription you have. If you received a notice regarding payment failure, it's possible your card has expired or something happened to it that the charge on it was denied by your card issuer. Please contact your card issuer to see what might have happened. You could update your card information by going to My Profile page and scroll down to "Credit Card On File" section.
Do you keep my credit card information at your site?
No, we don't keep your credit card information. We use a reputable, PCI compliant third-party to process your credit card. We encrypt your card information and send it over. You could always remove your credit card information completely by going to the Profile page and scroll down to the bottom. Then click the "Remove Card" button.
Do you have plans to add new functions to your site?
Yes, our dedicated and talented team of statisticians will continue to improve U-Design and add more functions to it. Please go to the Upcoming Products section for details.
What do I do if I encountered a problem?
Please let us know the problem you encountered by either emailing us: firstname.lastname@example.org or filling out the contact form at the bottom of each page.
- Ji, Y., Liu, P., Li, Y., & Nebiyou Bekele, B. (2010). A modified toxicity probability interval method for dose-finding trials. Clinical Trials, 7(6), 653-663.
- Ji, Y., & Wang, S. J. (2013). Modified toxicity probability interval design: a safer and more reliable method than the 3+ 3 design for practical phase I trials. Journal of Clinical Oncology, 31(14), 1785.
- Yang, S., Wang, S. J., & Ji, Y. (2015). An integrated dose-finding tool for phase I trials in oncology. Contemporary clinical trials, 45, 426-434.
- Guo, W., Wang, S. J., Yang, S., Lynn, H., & Ji, Y. (2017). A Bayesian interval dose-finding design addressingOckham's razor: mTPI-2. Contemporary clinical trials, 58, 23-33.
- O′Quigley, J., Pepe, M., & Fisher, L. (1990). Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics, 33-48.
- Storer, B. E. (1989). Design and analysis of phase I clinical trials. Biometrics, 925-937.
- Neuenschwander, B., Branson, M., & Gsponer, T. (2008). Critical aspects of the Bayesian approach to phase I cancer trials. Statistics in medicine, 27(13), 2420-2439.
- Ivanova, A., Flournoy, N., & Chung, Y. (2007). Cumulative cohort design for dose-finding. Journal of Statistical Planning and Inference, 137(7), 2316-2327.
- Guo W., Ji Y., and Li, D. R-TPI: Rolling Toxicity Probability Interval Design to Shorten the Duration and Maintain Safety of Phase I Trials. (Submitted) Journal of Biopharmaceutical Statistics.
- Skolnik, J. M., Barrett, J. S., Jayaraman, B., Patel, D., & Adamson, P. C. (2008). Shortening the timeline of pediatric phase I trials: the rolling six design. Journal of Clinical Oncology, 26(2), 190-195.
- Neuenschwander, B., Matano, A., Tang, Z., Roychoudhury, S., Wandel, S., & Bailey, S. (2015). A Bayesian industry approach to phase I combination trials in oncology. Statistical Methods in Drug Combination Studies, 2015, 95-135.
- Mander, A. P., & Sweeting, M. J. (2015). A product of independent beta probabilities dose escalation design for dual‐agent phase I trials. Statistics in medicine, 34(8), 1261-1276.