Pre-Clinical Dashboards

Our client was a clinical stage biopharmaceutical company, focusing on discovering and developing small molecule-based therapeutics. Our client required a service that enables elucidation of drug effectiveness and evaluation of ADME data sets.

Delivery

Arrayo leveraged its wealth of experience in delivering solutions to the biotech industry by identifying key client pain points and understanding functional requirements. A cloud native approach was implemented to allow for scalable and flexible development. A key highlight being the ability for users to test, upload and analyze in-house data in an ad-hoc manner, reducing data silos and additional overhead.

‘Napiergram’ is a comprehensive pharmaceutical data management and visualization platform developed to streamline preclinical drug development workflows. The solution addresses critical challenges in managing, analyzing, and predicting pharmacokinetic (PK) and toxicokinetic (TK) data from animal studies.

The solution centralized our client’s fragmented PK and TK data management through a robust web-based platform built on R Shiny architecture with PostgreSQL backend integration. Key capabilities included automated CSV data upload with template-driven validation, seamless integration with our client’s existing Collaborative Drug Discovery (CDD) platform, intelligent duplicate detection systems, and advanced visualization tools for dose-response analysis. The platform’s human dose prediction algorithms using allometric scaling principles enabled scientists to accelerate translation from preclinical animal studies to clinical development, while dynamic filtering and interactive Napiergram visualizations provided unprecedented insights into compound behavior across species and dosing regimens.

The implementation followed a phased approach over a 3-month timeline, beginning with requirements gathering and database schema design in weeks 1-2, followed by core platform development and CDD API integration in weeks 3-8. Critical milestones included successful deployment of the modular upload system with comprehensive error handling and validation logic, implementation of the visualization engine with real-time data filtering capabilities, and integration testing with existing CDD workflows to ensure seamless data flow. The final phase encompassed user acceptance testing, deployment to cloud infrastructure using containerized architecture, and comprehensive staff training on the new workflows. Throughout implementation, Arrayo maintained continuous stakeholder engagement through weekly progress reviews and iterative feedback incorporation, ensuring the final solution met all functional requirements while delivering measurable efficiency gains adhering to timeline and business goals.

Value

The Napiergram platform delivered transformative results for our client’s preclinical operations, achieving an 80% reduction in manual data processing time and eliminating data entry errors through automated validation systems. Scientists now access centralized historical data spanning multiple studies within seconds rather than hours, enabling rapid cross-compound comparisons and trend identification that previously required extensive manual compilation. The human dose prediction algorithms have accelerated preclinical-to-clinical transition planning by 40%, allowing stakeholders to make more informed go/no-go decisions earlier in the development process. Qualitatively, the platform established a single source of truth for all PK/TK data, significantly improving data integrity and regulatory compliance readiness, while the intuitive visualization tools have enhanced scientific collaboration and decision-making across research teams. The standardized data templates and automated CDD integration have eliminated the previous bottleneck of inconsistent data formats, resulting in seamless workflow integration that has improved overall research productivity and reduced the risk of costly data management errors that could impact regulatory submissions.

The project highlighted the critical importance of early stakeholder alignment on data validation rules, as initial assumptions about species/strain mapping requirements led to mid-project scope adjustments that extended the validation module development timeline. Integration complexity with legacy CDD systems proved more challenging than anticipated, requiring additional API error handling and data transformation logic to ensure robust connectivity. Future projects would benefit from more comprehensive upfront database schema validation and earlier prototyping of third-party integrations to identify potential compatibility issues before full-scale development begins.

This solution transforms our client’s approach to preclinical data management, providing a robust, scalable platform that accelerates drug development timelines while ensuring data quality and regulatory compliance.