Biology subjects

Collins, C. J.

Publications and source records attributed to Collins, C. J..

3 recordsLinked to original sources

bioRxiv2025

Fluidic Programmable Gravi-maze Array for High Throughput Multiorgan Drug Testing

The high attrition rate of drug candidates in clinical trials underscores the urgent need for more predictive preclinical models that accurately replicate human physiology. Traditional 2D cell cultures and animal models often fail to predict human responses due to their limited physiological relevance, particularly for biologics and immunotherapies involving complex multicellular and cross-organ interactions. This highlights the need for modeling and measurements of multiorgan interactions at higher throughput, prompting the development of multiorgan-on-a-plate platforms. Here, we present OrganRX, a modular, gravity-driven recirculation-based platform designed to imitate human organ function, physiological flow, immune cells circulation, and inter-organ communication in vitro. The Fluidic Programmable Gravi-maze Array (FPGA) technology integrates multiple organ models, including gut, liver, kidney, brain, tumor, and vascular compartments, within a microfluidic architecture designed to reproduce physiologically relevant shear stresses and gravity-driven recirculating flow that facilitates inter-organ communication. Using computational fluid dynamics (CFD) simulations and impedance-based flow validation, we confirmed accurate shear control across organ compartments. Organ-specific and multiorgan models were constructed using 3D extracellular matrix hydrogels and assessed for metabolism, toxicity, and senescence. Liver-kidney co-cultures demonstrated metabolic interplay via differential albumin and urea production. In addition, the platform was evaluated for biologics testing using immune-oncology models incorporating tumor spheroids, endothelial barriers, and circulating immune cells. Antigen-specific T-cells, checkpoint inhibitors, bispecific antibody and antibody-drug conjugate (ADC) studies demonstrated the ability to measure on-target tumor killing, off-target toxicity, cytokine release, and bystander effects across interconnected tissue compartments under dynamic recirculating conditions. The system enabled longitudinal evaluation of immune-mediated cytotoxicity, tissue-selective responses, and cross-organ signaling not readily captured in conventional static assays. Overall, the OrganRX platform offers a physiologically relevant, scalable, and automation-compatible platform for preclinical drug evaluation, biologics safety assessment, and disease modeling. Its ability to capture complex, dynamic inter-organ effects position it as a powerful tool for advancing translational research, mechanistic toxicology, and precision medicine.

bioengineering↗

bioRxiv2021

Bone mechanoregulation allows subject-specific load estimation based on time-lapsed micro-CT and HR-pQCT in vivo

Patients at high risk of fracture due to metabolic diseases frequently undergo long-term antiresorptive therapy. However, in some patients treatment is unsuccessful in preventing fractures or causes severe adverse health outcomes. Understanding load driven bone remodelling, i.e. mechanoregulation, is critical to understand which patients are at risk for progressive bone degeneration and may enable better patient selection or adaptive therapeutic intervention strategies. Bone microarchitecture assessment using high-resolution peripheral quantitative computed tomography (HR-pQCT) combined with computed mechanical loads has successfully been used to investigate bone mechanoregulation at the trabecular level. To obtain the required mechanical loads that induce local variances in mechanical strain and cause bone remodelling, estimation of physiological loading is essential. Yet, current models homogenise strain patterns throughout the bone to estimate load distribution in vivo, which may be a flawed assumption for investigating alterations in bone mechanoregulation. By further utilising available spatiotemporal information of time-lapsed bone imaging studies, we developed a mechanoregulation-based load estimation algorithm (MR). MR calculates organ scale loads by scaling and superimposing a set of predefined independent unit loads to optimise measured bone formation in high, quiescence in medium and resorption in low strain regions. We benchmarked our algorithm against a previously published load history algorithm (LH) using synthetic data, micro-CT images of murine vertebrae under defined experimental in vivo loadings and HR-pQCT images from seven patients. Our algorithm consistently outperformed LH in all three datasets. In silico generated time evolutions of distal radius geometries (n = 5) indicated significantly higher sensitivity, specificity, and accuracy for MR than LH (p < 0.01). This increased performance led to substantially better discrimination between physiological and extra-physiological loading in mice (n = 8). Moreover, a significantly (p < 0.01) higher association between remodelling events and computed local mechanical signals were found using MR (CCR = 0.42) than LH (CCR = 0.38) to estimate human distal radius loading. Future applications of MR may enable clinicians to link subtle changes in bone strength to changes in day-to-day loading, identifying weak spots in the bone micro-structure for local intervention and personalised treatment approaches.

bioengineering↗

bioRxiv2020

Automated Segmentation of Fractured Distal Radii by 3D Geodesic Active Contouring of in vivo HR-pQCT Images

Radius fractures are among the most common fracture types; however, there is limited consensus on the standard of care. A better understanding of the fracture healing process could help to shape future treatment protocols and thus improve functional outcomes of patients. High-resolution peripheral quantitative computed tomography (HR-pQCT) allows monitoring and evaluation of the radius on the micro-structural level, which is crucial to our understanding of fracture healing. However, current radius fracture studies using HR-pQCT are limited by the lack of automated contouring routines, hence only including small number of patients due to the prohibitively time-consuming task of manually contouring HR-pQCT images. In the present study, a new method to automatically contour images of distal radius fractures based on 3D morphological geodesic active contours (3D-GAC) is presented. Contours of 60 HR-pQCT images of fractured and conservatively treated radii spanning the healing process up to one year post-fracture are compared to the current gold standard, hand-drawn 2D contours, to assess the accuracy of the algorithm. Furthermore, robustness was established by applying the algorithm to HR-pQCT images of intact radii of 73 patients and comparing the resulting morphometric indices to the gold standard patient evaluation including a threshold- and dilation-based contouring approach. Reproducibility was evaluated using repeat scans of intact radii of 19 patients. The new 3D-GAC approach offers contours within inter-operator variability for images of fractured distal radii (mean Dice score of 0.992 {+/-} 0.004 versus median operator Dice score of 0.993 {+/-} 0.006). The generated contours for images of intact radii yielded morphometric indices within the in vivo reproducibility limits compared to the current gold standard. Additionally, the 3D-GAC approach shows an improved robustness against failure (n = 4) when dealing with cortical interruptions, fracture fragments, etc. compared with the automatic, default manufacturer pipeline (n = 40). Using the 3D-GAC approach assures consistent results, while reducing the need for time-consuming hand-contouring.

bioengineering↗