Accelerating drug discovery and development with Siemens pharma R&D solutions
Pharmaceutical research and development (R&D) faces a continuing problem: immense data generation coupled with persistent data silos. As new therapeutic pathways are discovered, the possibilities for developing medicines increase, but so does its complexity, making it more challenging for scientists to develop new lifesaving drugs and therapies.
Each new therapy requires selecting from thousands of molecules. Most of the time, the data generated during these stages is scattered across heterogeneous tools and unstructured records. This fragmentation hinders innovation, increases the burden on scientific teams and ultimately impacts the speed at which medicines become available to help patients.
In the age of AI, to properly manage and fully leverage this data, pharmaceutical companies need an industry-specific solution built for them, not a generic solution simply adapted to the sector.
The newest digital thread from Siemens leveraging solutions from Dotmatics, Drug Discovery and Development, supports the multi-phase process of identifying, testing and bringing new therapies to market – a journey that typically takes 10+ years and costs billions.
How data silos leave the AI promise unfulfilled
On average, one in a thousand drug candidates make it to market with 57% of scientists citing data silos as the biggest barrier to effective lab data use.1 This means critical insights remain hidden, leading to redundant experiments, increased costs and delayed progress.
Yet, AI has the potential to fundamentally transform the pharmaceutical industry. Yet, despite rising investment, the promise of AI in drug discovery and development often remains unfulfilled. Only 22% of pharma leaders have successfully scaled AI and only a mere 9% report meaningful returns.2
As a science-based industry, pharma scientists are always eager to learn more and discover and test new approaches that advance research and development. That’s why many recognize the potential of AI during drug discovery, especially in the application of biological sciences, which is key to successfully bringing more personalized treatments to patients.
Reliable AI is entirely dependent on structured scientific context and workflow representation. Without this foundation, its trust is limited to analyzing past data or fragmented data without full context, rather than guiding future experimentation and decision-making. A solid data foundation is critical to ensure data is being used accurately and the results are correct.
Connecting the entire drug development and discovery lifecycle
Most pharma organizations have digitized their scientific records, but digitizing is not the same as structuring. The critical need is for integrated digital solutions that ensure there are no isolated records with hidden insights.
The right solutions involve embedding scientific context directly into how work is performed, such as capturing intent, lineage and decisions at the source so that every experiment becomes a reusable, AI-ready asset. This should also encompass lab automation to unify scientific workflows, eliminate manual handoffs and ensure continuous, real-time data capture while increasing throughput and reducing variability.
Siemens has the full capability to connect the entire drug development lifecycle with an AI-ready data backbone, ensuring pharma organizations have the foundation that makes AI reliable, automation scalable and portfolio decisions faster and more confident.
Through the Comprehensive Digital Twin, Siemens provides pharma companies with the ability to combine the real and digital worlds across product and production lifecycles, enabling organizations to collect, connect, contextualize and transform data into confident, data-driven decisions in real-time.
Success story: How Pfizer de-risks formulation development
Pfizer faced the challenge of selecting optimal formulations for Phase 1 clinical trials and understanding the synergies between chemistry, manufacturing and control (CMC) and biopharmaceutics factors.
To de-risk formulation development through drug product performance modeling at preclinical stage, Pfizer used Siemens solutions to model oral absorption early in development and predict fractions absorbed across various physiological parameters and drug properties. This approach helped identify variability sources affecting in vivo performance across different patient populations.
The benefit? Pfizer can now consider biopharmaceutics risk factors at early stages, designing appropriate clinical trials for oral absorption and mitigating risks of failed trials. By developing strategies for optimal forumation, they can ensure fast progression to clinical stages without compromising performance.
Siemens: the leader in drug discovery and development solutions
Siemens has dedicated life sciences experts to build, create and carefully consider the specifications and requirements that meet the urgent needs of the pharma industry. With the acquisition of Dotmatics, Siemens is uniquely positioned to empower drug discovery and development leaders to transform their R&D operations via a unified, AI-ready data backbone that connects the entire drug development lifecycle. This turns data into actionable insights and speeds up the journey from concept to cure.
Siemens solution ensures rigorous data traceability to support regulatory compliance and quality management throughout the product lifecycle, an essential foundation for ultimately securing marketing authorization and bringing new therapies to patients.
AI-native, unified R&D platform (Luma)
Dotmatics’ Luma, now part of Siemens’ portfolio, is purpose-built for pharmaceutical R&D. This scientific intelligence platform is designed to:
- Connect diverse research systems by breaking down the silos that plague traditional R&D
- Harmonize structured and multimodal data to ensure all valuable data is aligned and not fragmented
- Automate workflows so scientists can focus on innovation and not manual tasks
- Apply AI to accelerate discovery and development providing scientists with predictive insights and guided experimentation
Luma empowers cross-domain collaboration, fostering an integrated R&D environment that ensures insights in one area instantly informing others.
Siemens and Dotmatics offers an unparalleled digital thread from molecule to market, starting with the initial drug discovery and development. By integrating Luma’s AI-native, unified R&D platform, Siemens strengthens its commitment to creating a Comprehensive Digital Twin for the entire pharmaceutical value chain.
Reliable, scalable and accessible AI and the Comprehensive Digital Twin
The Comprehensive Digital Twin combines the real and digital world, connecting design into one adaptive, executable model with integration and interoperability between systems. Siemens’ AI solutions generate insights from the vast amounts of data created across the R&D lifecycle, transforming it into actionable intelligence. For drug discovery, this means:
- Modeling, simulating and optimizing experiments and processes so scientists can validate decisions before committing valuable resources
- Predicting behaviors with accuracy with AI-powered foresight
- Taking a holistic view so scientists can make informed decisions based on a complete understanding of their drug candidates and processes
- Empowering informed, data-based decisions, moving beyond generic data science to insights rooted in the reality of your scientific processes
Regulatory compliance and data integrity
Because patient safety and outcomes are always at stake, pharma is one of the most highly regulated industries in the world making compliance and data integrity essential. Major benefits for quality and compliance initiatives can be achieved through Siemens solutions, including:
- Data integrity, traceability and audit readiness throughout the entire drug discovery and development process
- Automated documentation and electronic batch records, facilitating regulatory submissions and minimizing compliance risk
How Siemens creates a reliable and efficient drug discovery and development solution
As therapeutic modalities become increasingly complex, pharmaceutical companies face growing challenges in data management, collaboration and regulatory compliance. The traditional, fragmented ways of research and development are no longer viable.
Siemens has the tools, technology and experience in the pharma industry to cover the lifecycle from beginning to end, ensuring pharma organizations have the tools and solutions to make decisions quicker, release much-needed drugs and therapies to patients faster and use the most advanced power of science to help people live better lives.
According to a Frost & Sullivan report, “Siemens’ competitive advantage is in synergistic collaboration among its technical experts and cross functional teams, as together they deliver a top-notch customer purchase experience with its one-stop solutions, proprietary digital platform and software. With its unique proposition, Siemens can be considered ahead of its peers.”
FAQs about drug discovery and development solutions
1. What are the biggest challenges pharmaceutical companies face in drug discovery and development today?
Pharmaceutical companies grapple with immense data generation combined with persistent data silos. This fragmentation:
- Hinders innovation
- Increases the burden on scientific teams
- Slows down the delivery of new medicines
Additionally, while AI holds great promise, its potential is often unfulfilled due to the lack of structured scientific context and workflow representation.
2. How can pharma companies address the issue of data silos in pharmaceutical R&D?
Pharma organizations can tackle data silos by providing integrated digital solutions that embed scientific context directly into how work is performed. This includes capturing intent, lineage and decisions at the source, making every experiment a reusable, AI-ready asset.
Through the Comprehensive Digital Twin, which combines the real and digital worlds across product and production lifecycles, organizations are empowered to collect, connect, contextualize and transform data into confident, data-driven decisions in real-time.
3. How does Siemens leverage AI to accelerate drug discovery and development?
Siemens, with the acquisition of Dotmatics and its Luma platform, offers an AI-native, unified R&D platform purpose-built for pharmaceutical R&D, providing scientists with predictive insights and guided experimentation. This ensures AI is reliable, automation is scalable and portfolio decisions are faster and more confident.
