Speed Matters, Quality Matters

Shaping The Future Of Drug Development

A pioneering Software-as-a-Service biostatistics design web platform that delivers innovative optimized statistical designs to improve the efficiency, speed, and safety of drug development

POWERED BY

A team of world-class Bayesian statisticians, including PhDs from University of Chicago, University of Texas, Fudan University and Rice University, specializing in Bayesian adaptive designs and implementation for drug and device clinical trials

ANSWERING THE CALL

WHY U-Design?

Why U-Design
  • Features best-in-class innovative Bayesian adaptive designs based on years of research and continuous refinement that will improve safety, efficiency, and speed of clinical trials, and increase the probability of successful drug development programs
  • Offers a simple user interface that allows both clinicians and statisticians to easily create designs, run simulations and compare results with a few clicks of buttons
  • Automatically generates submission-ready protocol section related to designs and statistical plan

HOW IT WORKS

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.

1. What is the maximum sample size (total number of patients to be enrolled) of the trial?
2. What is the toxicity rate of the MTD? For example, if the MTD is defined as the highest dose with no more than 1 patient out of 6 having DLT, the toxicity rate of the MTD is 1/6, or 0.17.
3. How many dose levels will be investigated in the trial?
4. What Dose-finding design(s) do you want to implement?




CURRENT PRODUCTS

It's free to run up to 10 simulations for a scenario of any design!

Single
Agent

Cohort-Based Designs

An integrated tool supporting the simulation-based comparison among six main-stream dose-finding designs. This module provides both the modern Bayesian model-based designs, including 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 paint 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., submitted) that aim to accelerate phase 1 trials, and cohort-based designs (3+3 and mTPI-2 (Guo et al., 2017)). This module for rolling-based designs is the only tool on the market that incorporates the comparison of trial duration among different designs.

Single
Agent

(365) 400-2296

A simple-to-use tool that allows users 1) to generate and examine the transparent dose-finding decision tables for four designs, mTPI, mTPI-2, mCCD and 3+3, 2) to make the mTPI-2 decision of MTD selection based on accumulated data for a real trial.

Dual
Agent

806-289-3328

Combination drugs are important in oncology. By attacking the cancer at multiple points on cell signaling pathways, or by attacking multiple pathways, combination drugs can overcome resistance and gain greater potency. This module provides simulation-based comparison of two Bayesian model-based dose-finding designs, dual-agent BLRM (Neuenschwander et al., 2015) and PIPE (Mander and Sweeting, 2015). These two designs only model the toxicity outcomes and aim to identify the Maximum Tolerant Dose.

UPCOMING PRODUCTS

We are working hard to bring these to U-Design. Stay tuned!

A simple and effective dose-finding design for CAR-T phase I trials

Subgroup enrichment designs and methods for precision clinical trials

Adaptive dose insertion allowing new doses to be inserted during the trial to increase the probability of success (for finding the best dose)

A sample size calculator for dose-finding trials

832-748-7896The Bayesian Early-Phase Seamless Transformation Platform

The BEST platform provides a fast, efficient, and powerful solution for early-phase drug development. Currently, we offer BEST consulting services. We'll bring various designs and utilities under BEST to U-Design. Learn more about BEST

PRICING

It's free to run up to 10 simulations for a scenario of any design!

If you are an academic user, you could request a discount by sending an email to admin@laiyaconsulting.com from your organization email address with a subject line 'Academic Discount Request'. We will email you a discount code that you could enter at the checkout to enjoy a 30% discount off the regular subscription price, if you are eligible.

Individual Subscription Plans
Please follow below steps to purchase a subscription plan of interest:
  1. If you are not registered yet, please go to Registration page to complete registration. Registration is completely free.
  2. Log into your account
  3. Choose from below list of subscription plans and click "Get It" button of the chosen one
  4. In the resulting confirmation dialog box, click "Go To My Cart" button or later go to 7204001067 page directly by clicking "My Cart" menu item on the dropdown menu at the top right corner
  5. Once on My Cart page, follow instructions to fill in all necessary information and submit your credit card information to complete the purchase

Monthly
Subscription

$200 month

Full access to all designs

  • Single Agent
  • Dual Agents
  • Subgroup Design
  • Decision Tables

Semiannual
Subscription

$1,140 half year

Full access to all designs

  • Single Agent
  • Dual Agents
  • Subgroup Design
  • Decision Tables

Semiannual
Subscription

$2,160 year

Full access to all designs

  • Single Agent
  • Dual Agents
  • Subgroup Design
  • Decision Tables

Corporate Licenses

Please contact admin@laiyaconsulting.com to inquire about or purchase corporate licenses

We offer two options for corporate users – single user license and multi-user license. A single-user license allows one user to log in with the registered email address simultaneously. A multi-user license allows a number of users to log in with one or more registered email addresses simultaneously, depending on the number of licenses purchased.

For a multi-user license covering up to 5 users, the price is 50% off regular price (please see above prices under "individual subscription plans") for each user in addition to the first user (the first user is charged at regular subscription price). For a multi-user license covering more than 5 users, the price is 70% off regular price for each user in addition to the first 5 users (the first 5 users are charged according the multi-user license covering up to 5 users as described above).

U-Design USERS


And many more ...

FREQUENTLY ASKED QUESTIONS

REFERENCES

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. O'Quigley, J., Pepe, M., & Fisher, L. (1990). Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics, 33-48.
  6. Storer, B. E. (1989). Design and analysis of phase I clinical trials. Biometrics, 925-937.
  7. 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.
  8. Ivanova, A., Flournoy, N., & Chung, Y. (2007). Cumulative cohort design for dose-finding. Journal of Statistical Planning and Inference, 137(7), 2316-2327.
  9. 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.
  10. 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.
  11. 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.
  12. 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.

The Bayesian Early-Phase Seamless Transformation (BEST) Platform

We offer BEST consulting service.  Contact us to inquire about it

The Bayesian early-phase seamless transformation (BEST) platform provides a fast, efficient, and powerful solution for early-phase drug development. The BEST platform allows for 1) seamless transition from dose finding (Phase 1a) to cohort expansion (Phase 1b), and to a proof-of-concept (POC) stage (Phase 2a) if needed, 2) simultaneous expansion of multiple doses in multiple indications, 3) interim decision making to graduate or terminate a dose-indication arm adaptively, 4) powerful data analysis for RP2D selection, and 5) flexible selection of different modules tailored for customized design.

The statistical innovation of BEST centers at a proprietary Bayesian hierarchical model (BHM). With this model, BEST is able to empower a master protocol for early drug development that incorporates phase 1a and phase 1b into a single trial allowing for highly efficient exploration of efficacious and safe doses in multiple indications. Due to the novel BHM, the BEST platform can improve the overall study power in selecting the promising doses and indications for late-stage drug development and eliminate toxic or inefficacious doses quickly without wasting resources. This leads to increased probability of success for the entire drug development, speeds up the process, and reduces the cost for sponsors.

Features

  • Real-time monitoring of toxicity events
  • Real-time monitoring of probability of success
  • Acceleration in enrollment of highly-efficacious doses
  • Early exclusion of the inefficacious or overly-toxic doses

Benefits

  • Smaller sample size Compared to the conventional approach (independent frequentist test for each dose-indication arm), the BEST platform is able to save about 20%-30% sample size for the trial without sacrificing the chance of finding the efficacious doses and promising indications.
  • Higher power Compared to the conventional approach (independent frequentist test for each dose-indication arm), the BEST platform has a larger (up to twice many) chance to find the efficacious dose and promising indications.
  • Flexibility The BEST platform is highly flexible, allowing investigators to plan appropriate timing for recommending any promising dose-indication arm as RP2D during the cohort expansion, and to early stop.
  • Time-saving BEST accelerates drug development due to the seamless strategy and sample size reduction.

BEST PRODUCTS

The BEST platform incorporates a suite of innovative, efficient designs and utilities for different objectives.

Solution Suites

Designs Under BEST

  • The mTPI-2 design (modified Toxicity Probability Interval Design version 2, Guo et al., 2017a): a simple, safe and efficient phase 1 dose finding design, in which all decisions can be transparently tabulated for examination before trial begins.
  • R-TPI (Rolling Toxicity Probability Interval Design, Guo et al., 2018): a fast and efficient phase 1 dose finding trial, that incorporates a rolling enrollment scheme, aiming to accelerate the trial conduct without sacrificing safety and desirability.
  • PITE (Probability Interval Design based on both Toxicity and Efficacy): a transparent, efficient and powerful solution for immuno-oncology (IO) phase 1 dose finding trials, which incorporates efficacy outcomes together with toxicity outcomes to inform dosing decisions to optimize efficacy and safety simultaneously.
  • Dual-agent Drug Combination Dose Finding designs: the state-of-art designs such as the AAA design (Lyu et al., 2018) in which multiple adaptive scheme (e.g. adaptive dose insertion and parallel patient enrollment at multiple doses) can be incorporated.
  • MUCE (MUltiple Cohort Expansion): the key feature of BEST platform that allows for expansion of multiple doses in multiple indications. With the innovative BHM, MUCE is able to save the patient resources without sacrificing the chance of finding the efficacious doses and indications.
  • SCUBA (Subgroup ClUster Based Bayesian Adaptive Design, Guo et al., 2017b): a powerful precision-medicine solution for phase 2 subgroup enrichment trials aiming to find optimal subgroups that benefit from precise treatment and increase the probability of success for the whole trial.

Other Utilities Under BEST

  • Sequential or seamless transition from dose finding to cohort expansion.
  • Sequential or seamless transition from cohort expansion to POC.
  • Interim analysis that allows early stopping for futility, superiority, or toxicity.
  • Comparison with different reference rates for different indications.
  • Flexible sample size calculation for the entire master protocol or for each component such as dose finding only, or cohort expansion only.
  • Adaptive or equal randomization across different doses during cohort expansion.

7575174794

778-507-6936

REFERENCES

  1. Guo, W., Wang, S. J., Yang, S., Lynn, H., & Ji, Y. (2017a). A Bayesian interval dose-finding design addressing Ockham's razor: mTPI-2. Contemporary clinical trials, 58, 23-33.
  2. Guo, W., Ji, Y., & Li, D. (2018). R-TPI: Rolling Toxicity Probability Interval Design to Shorten the Duration and Maintain Safety of Phase I Trials. Journal of Biopharmaceutical Statistics.
  3. Lyu, J., Ji, Y., Zhao, N., & Catenacci, D. V. (2018). AAA: triple adaptive Bayesian designs for the identification of optimal dose combinations in dual‐agent dose finding trials. Journal of the Royal Statistical Society: Series C (Applied Statistics).
  4. Guo, W., Ji, Y., & Catenacci, D. V. (2017b). A subgroup cluster‐based Bayesian adaptive design for precision medicine. Biometrics, 73(2), 367-377.