Adaptive informatics for multifactorial and high-content biological data.

Whereas genomic data are universally machine-readable, data from imaging, multiplex biochemistry, flow cytometry and other cell- and tissue-based assays usually reside in loosely organized files of poorly documented provenance. This arises because the relational databases used in genomic research are difficult to adapt to rapidly evolving experimental designs, data formats and analytic algorithms. Here we describe an adaptive approach to managing experimental data based on semantically typed data hypercubes (SDCubes) that combine hierarchical data format 5 (HDF5) and extensible markup language (XML) file types. We demonstrate the application of SDCube-based storage using ImageRail, a software package for high-throughput microscopy. Experimental design and its day-to-day evolution, not rigid standards, determine how ImageRail data are organized in SDCubes. We applied ImageRail to collect and analyze drug dose-response landscapes in human cell lines at single-cell resolution.

Model-Informed Drug Development of the Masked Anti-PD-L1 Antibody CX-072.

CX-072 is an anti-PD-L1 (programmed death ligand 1) Probody therapeutic (Pb-Tx) designed to be preferentially activated by proteases in the tumor microenvironment and not in healthy tissue. Here, we report the model-informed drug development of CX-072. A quantitative systems pharmacology (QSP) model that captured known mechanisms of Pb-Tx activation, biodistribution, elimination, and target engagement was used to inform clinical translation. The QSP model predicted that a trough level of masked CX-072 (intact CX-072) of 13-99 nM would correspond to a targeted, 95% receptor occupancy in the tumor. The QSP model predictions appeared consistent with preliminary human single-dose pharmacokinetic (PK) data following CX-072 0.03-30.0 mg/kg as monotherapy: CX-072 circulated predominantly as intact CX-072 with minimal evidence of target-mediated drug disposition. A preliminary population PK (POPPK) analysis based upon 130 subjects receiving 0.03-30.0 mg/kg as monotherapy included a provision for a putative time-dependent and dose-dependent antidrug antibody (ADA) effect on clearance (CL) with a mixture model. Preliminary POPPK estimates for intact CX-072 time-invariant CL and volume of distribution were 0.306 L/day and 4.84 L, respectively. Exposure-response analyses did not identify statistically significant relationships with best change from baseline sum of measurements and either adverse events of grade ≥ 3 or of special interest. Simulations suggested that > 95% of patients receiving CX-072 10 mg/kg every two weeks would exceed the targeted trough level regardless of ADA, and that dose adjustment by body weight was not necessary, supporting a fixed 800 mg dose for evaluation in phase II.

Flexible informatics for linking experimental data to mathematical models via DataRail.

MOTIVATION: Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all normalization, scaling, and fusion routines used to assemble the training data from primary results. RESULTS: We describe the implementation of DataRail, an open source MATLAB-based toolbox that stores experimental data in flexible multi-dimensional arrays, transforms arrays so as to maximize information content, and then constructs models using internal or external tools. Data integrity is maintained via a containment hierarchy for arrays, imposition of a metadata standard based on a newly proposed MIDAS format, assignment of semantically typed universal identifiers, and implementation of a procedure for storing the history of all transformations with the array. We illustrate the utility of DataRail by processing a newly collected set of approximately 22 000 measurements of protein activities obtained from cytokine-stimulated primary and transformed human liver cells. AVAILABILITY: DataRail is distributed under the GNU General Public License and available at http://code.google.com/p/sbpipeline/

Quantitative Systems Pharmacology Model of a Masked, Tumor-Activated Antibody.

PROBODY therapeutics (Pb-Tx) are protease-activatable prodrugs of monoclonal antibodies (mAbs) designed to target tumors where protease activity is elevated while avoiding normal tissue. They are composed of a parental mAb, a mask that inhibits antibody binding to target, and a protease-cleavable substrate between the mask and the mAb. We report a quantitative systems pharmacology model for the rational design and clinical translation of Pb-Tx. The model adequately described monkey pharmacokinetic data following the administration of six anti-CD166 Pb-Tx of varying mask strength and substrate cleavability and captured the trend of decreasing Pb-Tx systemic clearance with increasing mask strength. Projections to humans suggested both higher levels of Pb-Tx in tumor relative to parental mAb and an optimal mask strength for maximizing tumor receptor-mediated uptake. Simulations further suggested the majority of circulating species in humans would be intact/masked Pb-Tx, with no significant flux of cleaved/activated species from tumor to the systemic compartment.

Quantitative Systems Pharmacology Model of hUGT1A1-modRNA Encoding for the UGT1A1 Enzyme to Treat Crigler-Najjar Syndrome Type 1.

Crigler-Najjar syndrome type 1 (CN1) is an autosomal recessive disease caused by a marked decrease in uridine-diphosphate-glucuronosyltransferase (UGT1A1) enzyme activity. Delivery of hUGT1A1-modRNA (a modified messenger RNA encoding for UGT1A1) as a lipid nanoparticle is anticipated to restore hepatic expression of UGT1A1, allowing normal glucuronidation and clearance of bilirubin in patients. To support translation from preclinical to clinical studies, and first-in-human studies, a quantitative systems pharmacology (QSP) model was developed. The QSP model was calibrated to plasma and liver mRNA, and total serum bilirubin in Gunn rats, an animal model of CN1. This QSP model adequately captured the observed plasma and liver biomarker behavior across a range of doses and dose regimens in Gunn rats. First-in-human dose projections made using the translated model indicated that 0.5 mg/kg Q4W dose should provide a clinically meaningful and sustained reduction of >5 mg/dL in total bilirubin levels.

Quantitative systems toxicology.

The overarching goal of modern drug development is to optimize therapeutic benefits while minimizing adverse effects. However, inadequate efficacy and safety concerns remain to be the major causes of drug attrition in clinical development. For the past 80 years, toxicity testing has consisted of evaluating the adverse effects of drugs in animals to predict human health risks. The U.S. Environmental Protection Agency recognized the need to develop innovative toxicity testing strategies and asked the National Research Council to develop a long-range vision and strategy for toxicity testing in the 21st century. The vision aims to reduce the use of animals and drug development costs through the integration of computational modeling and in vitro experimental methods that evaluates the perturbation of toxicity-related pathways. Towards this vision, collaborative quantitative systems pharmacology and toxicology modeling endeavors (QSP/QST) have been initiated amongst numerous organizations worldwide. In this article, we discuss how quantitative structure-activity relationship (QSAR), network-based, and pharmacokinetic/pharmacodynamic modeling approaches can be integrated into the framework of QST models. Additionally, we review the application of QST models to predict cardiotoxicity and hepatotoxicity of drugs throughout their development. Cell and organ specific QST models are likely to become an essential component of modern toxicity testing, and provides a solid foundation towards determining individualized therapeutic windows to improve patient safety.

Autocrine signaling is a key regulatory element during osteoclastogenesis.

Osteoclasts are responsible for bone destruction in degenerative, inflammatory and metastatic bone disorders. Although osteoclastogenesis has been well-characterized in mouse models, many questions remain regarding the regulation of osteoclast formation in human diseases. We examined the regulation of human precursors induced to differentiate and fuse into multinucleated osteoclasts by receptor activator of nuclear factor kappa-B ligand (RANKL). High-content single cell microscopy enabled the time-resolved quantification of both the population of monocytic precursors and the emerging osteoclasts. We observed that prior to induction of osteoclast fusion, RANKL stimulated precursor proliferation, acting in part through an autocrine mediator. Cytokines secreted during osteoclastogenesis were resolved using multiplexed quantification combined with a Partial Least Squares Regression model to identify the relative importance of specific cytokines for the osteoclastogenesis outcome. Interleukin 8 (IL-8) was identified as one of RANKL-induced cytokines and validated for its role in osteoclast formation using inhibitors of the IL-8 cognate receptors CXCR1 and CXCR2 or an IL-8 blocking antibody. These insights demonstrate that autocrine signaling induced by RANKL represents a key regulatory component of human osteoclastogenesis.

Akt and ERK control the proliferative response of mammary epithelial cells to the growth factors IGF-1 and EGF through the cell cycle inhibitor p57Kip2.

Epithelial cells respond to growth factors including epidermal growth factor (EGF), insulin-like growth factor 1 (IGF-1), and insulin. Using high-content immunofluorescence microscopy, we quantitated differences in signaling networks downstream of EGF, which stimulated proliferation of mammary epithelial cells, and insulin or IGF-1, which enhanced the proliferative response to EGF but did not stimulate proliferation independently. We found that the abundance of the cyclin-dependent kinase inhibitors p21Cip1 and p57Kip2 increased in response to IGF-1 or insulin but decreased in response to EGF. Depletion of p57Kip2, but not p21Cip1, rendered IGF-1 or insulin sufficient to induce cellular proliferation in the absence of EGF. Signaling through the PI3K (phosphatidylinositol 3-kinase)-Akt-mTOR (mammalian target of rapamycin) pathway was necessary and sufficient for the increase in p57Kip2, whereas MEK [mitogen-activated or extracellular signal-regulated protein kinase (ERK) kinase]-ERK activity suppressed this increase, forming a regulatory circuit that limited proliferation in response to unaccompanied Akt activity. Knockdown of p57Kip2 enhanced the proliferative phenotype induced by tumor-associated PI3K mutant variants and released mammary epithelial acini from growth arrest during morphogenesis in three-dimensional culture. These results provide a potential explanation for the context-dependent proliferative activities of insulin and IGF-1 and for the finding that the CDKN1C locus encoding p57Kip2 is silenced in many breast cancers, which frequently show hyperactivation of the PI3K pathway. The status of p57Kip2 may thus be an important factor to assess when considering targeted therapy against the ERK or PI3K pathways.