Preclinical Drug Testing in Scalable 3D Engineered Muscle Tissues

Accurately modeling healthy and disease conditions in vitro is vital for the development of new treatment strategies and therapeutics. For cardiac and skeletal muscle diseases, contractile force and kinetics constitute key metrics for assessing muscle function. New and improved methods for generating engineered muscle tissues (EMTs) from induced pluripotent stem cells have made in vitro disease modeling more reliable for contractile tissues; however, reproducibly fabricating tissues from suspended cell cultures and measuring their contractility is challenging. Such techniques are often plagued with high failure rates and require complex instrumentation and customized data analysis routines. A new platform and device that utilizes 3D EMTs in conjunction with a label-free, highly-parallel, and automation-friendly contractility assay circumvent many of these obstacles. The platform enables facile and reproducible fabrication of 3D EMTs using virtually any cell source. Tissue contractility is then measured via an instrument that simultaneously measures 24 tissues without the need for complex software analysis routines. The instrument can reliably measure micronewton changes in force, allowing for dose-dependent compound screening to measure the effect of a drug or therapeutic on contractile output. Engineered tissues made with this device are fully functional, generating twitch and tetanic contractions upon electrical stimulation, and can be analyzed longitudinally in culture over weeks or months. Here, we show data from cardiac muscle EMTs under acute and chronic dosing with known toxicants, including a drug (BMS-986094) that was pulled from clinical trials after patient fatalities due to unanticipated cardiotoxicity. Altered skeletal muscle function in engineered tissues in response to treatment with a myosin inhibitor is also presented. This platform enables the researcher to integrate complex, information-rich bioengineered model systems into their drug discovery workflow with minimal additional training or skills required.