Specialize in novel and pragmatic approaches for designing clinical trials, and aim to transform the early-phase drug development with forward-looking vision and cutting-edge statistical methods.
We possess expertise in cancer genomics, computational biology, and bioinformatics.
We provide powerful precision medicine approaches to enable precise subgroup findings for clinical trial data.
Laiya provides advanced analytics models, including deep neural networks, machine learning, and Bayesian models for solving big/small data problems in health and non-health fields.
LAIYA is an innovative and intelligent solution provider for new drug development. We specialize in Bayesian adaptive designs and implementation for drug and device clinical trials. Our mission is to develop the best-in-class adaptive designs, strategies, and integrated software platforms to lower the risk of clinical trial failure, improve the probability of success, accelerate the development process, and maximize portfolio returns.
Founded by a tenured professor of University of Chicago, Laiya has been a leading innovator in the application of Bayesian adaptive designs to clinical trials. Our team of world class Bayesian statisticians include PhDs from University of Texas, Fudan University and Rice University. Our work was published in top journals such as Nature Methods, Journal of Clinical Oncology, Journal of the National Cancer Institute, and has won several international awards:
Laiya found wide recognition not only in the academic field but also in the industry. Many of its research initiatives have been developed into successful commercial products that were adopted by well-known global pharmaceutical companies, and FDA has approved clinical trial protocols incorporating these products.
U-Design is a web-based next-generation statistical and informatics tool kit for Phase I clinical trial design
The Bayesian early-phase seamless transformation (BEST) platform provides a fast, efficient, and powerful solution for early-phase drug development.
Modified Toxicity Probability Interval Design Version 2
Rolling Toxicity Probability Interval Design
Probability Interval Design based on both Toxicity and Efficacy
Multiple Doses/Multiple Indications Cohort Expansion
Dual-agent Drug Combination Dose Finding Design
Subgroup Cluster Based Bayesian Adaptive Design for Precision Medicine
A proposal to transform phase 1 oncology trials at company xyz Laiya Consulting, Inc. September 28, 2019 Purpose: To promote the use of a novel phase 1 trial design suite that tailors to the modern needs of phase 1 clinical trials in oncology. Introduction: Based on a set of innovative statistical designs and approaches, Laiya[…]
Position: Junior / Senior Statistician (with focus on methodology development and application) Education: PhD in statistics, biostatistics, mathematics, or equivalent, open for fresh PhD Responsibilities: Develop novel statistical methods (especially in the Bayesian adaptive designs) for real-world clinical trials. Study existing statistical literature on clinical trial methodology and practical challenges in drug clinical trials. Attend[…]
Congratulations to Dr. Lyu for winning a second-place award of student posters in 2019 DIA China annual meeting. The 2019 DIA China annual meeting was held successfully at the Beijing Convention Center from 05/21 – 05/23, 2019. Laiya Consulting’s statistician Dr. Lyu won the second place award of student posters for her work titled “MUCE:[…]
Laiya founder Yuan Ji, Professor of Biostatistics at The University of Chicago, presented a poster entitled “The i3+3 Design for Phase I Clinical Trials” at 2019 ASCO Annual Meeting in Chicago, USA. The i3+3 design is the first rule-based dose-finding design with a performance in par with model-based designs like mTPI and mTPI-2. The paper[…]