Accelerating Computational Drug Design with CDD Vault: A Molecular Forecaster Case Study

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Introduction to Molecular Forecaster Inc.

Molecular Forecaster Inc. (MFI) is a pioneering computational chemistry company helping organizations make smarter decisions in small-molecule drug design. With expertise in quantum mechanics, molecular dynamics, chemoinformatics, and AI, MFI combines proprietary software with contract research services to support pharma, biotech, and academic partners.

As its partnerships grew in number and complexity, MFI required a modern data infrastructure to scale collaboration and ensure secure, structured data management. This case study explores how CDD Vault transformed MFI’s workflows—driving efficiency, enabling real-time collaboration, and supporting AI-powered insight generation.

Findings: A Need for Centralized, Secure Collaboration in Drug Discovery

Initially, MFI relied on spreadsheets and manual data transfers to coordinate across research teams—a method prone to errors and inefficiency. Issues like copy-paste mistakes, versioning confusion, and data silos led to concerns over data integrity. As projects multiplied, so did the friction. MFI sought a flexible, collaborative platform with powerful data handling capabilities. After evaluating alternatives, the company adopted CDD Vault for its secure infrastructure, collaborative design, and strong industry reputation.

“The central repository we have with CDD Vault is so much more efficient than tracking spreadsheets as we previously had to do.”

— Josh Pottel, Ph.D., President and CEO, Molecular Forecaster Inc.

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A Secure “Single Source of Truth” for Project-Based Collaboration

MFI now structures its CDD Vault environment by creating dedicated vaults for each client or project. This compartmentalization maintains strict data privacy while centralizing all relevant chemical, biological, and computational data in one accessible location.

Problem: Fragmented, spreadsheet-based workflows created version control issues and collaboration slowdowns.
Solution: CDD Vault enabled project-specific data isolation while maintaining a central repository for reliable access.

“CDD Vault provides a way in which we can centralize all the data that we get from different assays, experiments, simulations, and other work.”

— Mihai Burai-Pătrașcu, Ph.D., Director, Computer-Aided Drug Design

Supporting a Multidisciplinary Drug Discovery Pipeline

From quantum chemists to structural biologists, MFI’s team operates across disciplines and collaborates with external academic and CRO partners. Whether simulating protein structures or validating experimental assays, CDD Vault offers a unified platform where diverse specialists can access, interpret, and share data securely—accelerating the design–make–test–analyze (DMTA) cycle.

MFI’s public-private partnerships (like its work with McGill University and TransBioTech) depend on real-time access to shared data such as solubility metrics, binding data, and functional readouts—all made possible through CDD Vault.

“With CDD Vault, researchers with different expertise can look at the same data differently. The more we can share all the information, the better we can derive the most knowledge from it.”

— Josh Pottel, Ph.D.

Ideation with AI: CDD Vault’s Bioisosteres and Similarity Search

The CDD Vault AI module plays a critical role in sparking new ideas. MFI uses it to explore generative bioisosteres—machine-suggested analogs of active compounds—and run ultrafast similarity searches against ChEMBL, SureChEMBL, and Enamine databases. This integration supports faster structure-activity relationship (SAR) decisions and better compound prioritization for synthesis or purchase.

Example Workflow:

Run a virtual screen to identify promising hits.
Use CDD Vault AI to generate close analogs.
Compare compound properties and predict behavior.
Select top candidates for synthesis and testing.

“We can look for close analogs and compare different properties, then suggest better compounds for SAR testing.”

— Mihai Burai-Pătrașcu, Ph.D.

AI + AlphaFold2 Integration for Predictive Protein Modeling

When structural data is missing or incomplete, MFI leverages CDD Vault’s integration with NVIDIA BioNeMo’s AlphaFold2, enabling fast generation of protein models to advance drug discovery efforts.

From predicting novel conformations to offering fresh starting points for docking and simulations, this integration gives researchers more “shots on goal,” especially when targets lack resolved structures.

“AlphaFold2 will generate you a structure when none exists. It gives us another perspective and way to move forward.”

— Josh Pottel, Ph.D.

Conclusion

CDD Vault has become a cornerstone of MFI’s drug discovery informatics strategy. With project-specific vaults, AI-powered design support, and seamless partner collaboration, MFI eliminated data chaos and streamlined innovation. From foundational structure modeling to high-throughput SAR exploration, CDD Vault provides a flexible, reliable platform for managing complex research workflows.

Recommendations

For organizations managing contract research, academic partnerships, or multidisciplinary data in drug discovery, CDD Vault offers a robust alternative to spreadsheets and siloed systems. Its integration-ready platform, AI modules, and strong collaboration tools make it ideal for any company seeking scalable, secure infrastructure for modern R&D.

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