Toward simulation-guided chemistry: integrating computational and experimental approaches in India

India’s aspirations for clean energy, sustainable materials and a robust bioeconomy are increasingly driven by advancements in chemistry. Sectors such as biomass valorisation, green solvent design, smart materials and precision therapeutics are central to the country’s developmental and environmental goals. However, a persistent challenge exists in translating fundamental discoveries with a low technology readiness level (TRL 1-3) into scalable, applied technologies (TRL 4-6). This gap is further exacerbated by the lack of a comprehensive framework to foster multidisciplinary initiatives for accelerating technological innovation, reducing inefficiencies in research pipelines, minimising redundant experimentation and enhancing foresight in early-stage R&D planning. Building such a framework is critical for ensuring greater visibility, competitiveness and translational potential for research outcomes. 

Computational tools, including quantum mechanical calculations, molecular dynamics simulations, and AI-assisted molecular design offer a powerful tool to bridge this gap between discovery and deployment. These methods have shortened discovery cycles, reduced costs and facilitated the design of safer, more sustainable molecules. Yet despite this global momentum, computational and experimental chemistry are often siloed in India’s research ecosystem, leading to fragmented progress and under-optimised investment in R&D. 

The challenge is further compounded by disparities in institutional capacity. While selected national labs and elite institutions acknowledge the importance of such integration and possess advanced simulation infrastructures, the majority of tier-2 and tier-3 universities lack access to computational tools, infrastructure or training. This asymmetry prevents many researchers from contributing to, or benefiting from simulation-informed innovation, thereby reinforcing regional and institutional divides in scientific output. Moreover, students have limited exposure to programming languages and basic computational skills at school and undergraduate levels, creating a long-term skills gap in chemistry education. 

Bridging these divides is not only essential for accelerating innovation but also for embedding anticipatory governance into India’s R&D. Simulation-based approaches can help identify dual-use risks, minimise toxicity and inform regulatory readiness before technologies scale. Importantly, integrating computational and experimental domains across institutions offers India an opportunity to align its innovation goals with global standards of sustainability, equity and safety, while empowering a wider spectrum of researchers to contribute to national scientific and technological priorities.

A national policy framework is needed that systematically integrates computational tools with experimental chemistry, democratises simulation access and cultivates a future-ready, interdisciplinary scientific workforce to transform fundamental chemistry into real-world solutions. Thus, we propose the establishment of a National Centre for Integrated Molecular Design (NCIMD), a distributed public infrastructure that will serve as both a technical and educational backbone for the country’s chemical sciences ecosystem. 

The NCIMD would provide access to advanced modelling and simulation tools, deliver structured training modules for students and researchers, build seamless school-to-lab education pathways to inculcate computational thinking and support simulation-informed experimental research across academia, national labs and industrial sectors, enabling predictive design to guide synthesis, scale-up and applications across various sectors. By embedding such a policy framework aligned with principles of sustainability, equity and anticipatory governance in chemical sciences, India can broaden participation in deeptech innovation and secure a position globally in responsible, simulation-guided technology development within a more agile and resource-efficient ecosystem.

Context and rationale

Chemical science lies at the heart of India’s strategic and developmental ambitions. Whether it is the transition to a green hydrogen economy, the development of biodegradable polymers, the quest for affordable medicines or the optimisation of carbon capture utilisation and storage (CCUS), chemistry plays a foundational role.

Within these domains, there is a dire need to accelerate the innovation pipeline from early-stage research to scalable, market-ready solutions.  Globally, this gap is being addressed through deliberate integration of simulation-guided approaches into both public and private sector R&D pipelines. The EU’s European Materials Modelling Council (EMMC) links industrial needs with academic simulation capabilities through collaborative platforms and data-sharing standards. South Korea’s National Supercomputing Centre provides cloud-based modelling resources to universities and industries alike, accelerating research in battery chemistry, photonics, and drug delivery. In the US, initiatives such as the Materials Genome Initiative and the Defence Advanced Research Projects Agency’s Accelerated Molecular Discovery programme are embedding AI and computational modelling in the discovery process.

In contrast, India’s landscape remains uneven. While leading institutions such as the Indian Institute of Science (IISc), the Indian Institutes of Technology (IITs) and selected national laboratories have made significant advances in computational chemistry, molecular modeling and quantum simulation, these efforts are highly localised and do not translate into systemic change. The absence of a national policy framework or dedicated institutional mechanism for simulation-guided research perpetuates redundancy, wasted time and resources, inconsistent scaling and delays in technology readiness transitions. With recent grants emphasising the collaboration of academia with industries, the computational component also needs to be introduced as a mandate for public R&D grants to overcome the current issues of marginalisation in institutional planning. This fragmentation is especially pronounced in India’s tier-2 and tier-3 institutions, which constitute most of the country’s scientific and educational infrastructure. These institutions often lack high-performance computing (HPC) facilities or suitably trained personnel, creating barriers that put these powerful tools out of researchers’ reach. This not only limits the country’s research output but also reinforces structural inequities within the scientific ecosystem.

Beyond academia, India’s deeptech startup ecosystem, particularly in the domains of biotech, green chemistry and sustainable manufacturing, faces similar constraints. Startups operating at TRL 4–6 stages require rapid prototyping, optimisation and validation cycles. Without access to affordable and scalable modelling support, they must rely exclusively on physical experimentation, which is time-consuming, expensive and investor-sensitive, slowing down innovation and commercialisation.

The case for simulation-guided chemistry has a broader governance rationale. As chemistry converges with frontier areas such as AI-driven molecule design, lab-grown food systems and programmable materials, the associated ethical, environmental and dual-use risks of emerging technologies are becoming harder to anticipate using conventional assessment methods. Simulation and modelling provide a proactive pathway to evaluate performance, toxicity and sustainability prior to physical deployment. For instance, in synthetic biology or Crispr applications, computational modelling can forecast off-target effects, enabling regulators to act pre-emptively rather than reactively. Moreover, India’s ambitions to play a larger role in international standard-setting and regulatory diplomacy, whether in green chemistry, chemical weapons control, and nano-governance, demand robust foresight capabilities built on data-driven and simulation-based insights. Thus, this is not just a technical need but a strategic lever for science diplomacy and global leadership.

Finally, the talent pool comprising the students at the undergraduate and school levels must be addressed, who presently encounter chemistry as a purely experimental or theoretical discipline, with minimal exposure to data-driven or simulation-based methods. This creates a long-term talent bottleneck, preventing future researchers, policymakers and entrepreneurs from implementing the interdisciplinary nature of 21st-century chemical science. Integrating computational chemistry into early science education through curriculum reforms, hands-on module, and access to open-source platforms can help cultivate a generation of learners fluent in both molecular science and digital reasoning.

The rationale for a national policy on simulation-guided chemistry is therefore threefold. First, it fulfils scientific needs: improving research efficiency, predictive accuracy and translational success across multiple domains. Second, it addresses structural equity: democratising access to computational tools and reducing disparities across institutions to participate in cutting-edge R&D. Third, it meets a governance imperative: to build anticipatory regulatory capabilities, strengthen ethical oversight, and position India as a global leader in responsible and simulation-enabled innovation. 

The policy idea 

To bridge the persistent gap between computational and experimental chemistry in India, we propose the creation of NCIMD, a distributed, multi-tiered public infrastructure initiative under the Ministry of Science and Technology. This mission-mode programme would systematically embed simulation-guided research into India’s chemistry ecosystem by combining four key levers: digital infrastructure, human capacity-building, education and anticipatory governance within a unified national framework.

The core objective of NCIMD is to facilitate integration of computational modelling and simulation approaches across academia, industry and regulatory institutions, thereby accelerating innovation, reducing R&D inefficiencies and strengthening India’s capacity for sustainable research. NCIMD would operate through four mutually reinforcing pillars:

Pillar 1: Nationwide access to modelling infrastructure 

NCIMD will provide a shared, cloud-based platform offering equitable, nationwide access to high-performance computational tools, including quantum and semi-empirical methods, molecular dynamics simulations, quantum chemical solvers, machine learning-based tools, including drug discovery pipelines and environmental toxicity prediction models. This platform would leverage existing infrastructure under the National Supercomputing Mission (NSM), the Centre for development of Advnaced Computing (CDAC), CSIR-4PI, and private cloud providers, while prioritising open-source software solutions such as  GROMACS, NAMD, LAMMPS, DL_POLY, ORCA, and OpenMM to overcome licensing burdens. The key features will include:

• Capacity building programmes and skill set enhancement programs for young researchers
• Pre-configured simulation toolkits with user-friendly interfaces
• Shared virtual labs with standard templates for common chemical workflows
• Tiered access models: free basic access for academic users, subsidised advanced access for startups and R&D- intensive industries 

Pillar 2: Distributed network of regional hubs 

Rather than a single centralised institution, NCIMD would adopt a distributed hub-and-spoke model, anchored by regional centres hosted at leading institutions (for example: IITs, NITs, IISERs, CSIR). This structure will ensure that simulation-guided research is not limited to elite institutions but becomes a shared national resource. The core functions of the hubs will include:

• Technical support and training for researchers 
• Pilot projects integrating wet-lab and dry-lab workflows
• Industry partnerships for experimental validation and scale-up
• Special thematic clusters focused on priority areas such as biomass valorisation, hydrogen production, new-generation batteries, pharmaceuticals, green materials and carbon capture technologies

Pillar 3: National simulation curriculum and training programme 

To address long-term capacity building, NCIMD will work with the University Grants Commission (UGC), All India Council for Technical Education (AICTE) and the National Council of Educational Research and Training (NCERT) to embed computational chemistry and simulation literacy into the national science curriculum from secondary school through to undergraduate and postgraduate levels. Programme components will include: 

• School-level modules introducing chemical modeling through gamified visual simulations
• Undergraduate lab courses integrating simulation with experimental data analysis 
• Postgraduate certification programmes on advanced computational workflows
• Short-term faculty development and industry refresher courses
• Multilingual online MOOC learning platforms with interactive assignments and cloud-based hands-on practice 

The goal is to cultivate a future-ready scientific workforce fluent in both molecular science and digital reasoning. 

Pillar 4: Pilot project grants and innovation challenge funds 

NCIMD will act as a catalyst for innovation by funding simulation-informed research projects in two modes:

• Integration grants: targeted support for research teams integrating computational and experimental approaches across TRL 1–6, with priority for consortia that include tier-2/3 colleges or MSMEs.
• Innovation challenge funds: Inviting applications focused on thematic areas addressing national priorities such as catalyst design for green fuels, safe agrochemicals, CCUS technologies, with funding to advance ideas into working prototypes.

This approach will incentivise risk-taking, foster collaboration and create proof-of-concept project demonstrations showcasing the power of predictive modelling. 

NCIMD is the first of its kind platform to provide unified integration of theory and experiments, moving beyond disciplinary silos to co-develop predictive models and experimental validation. Secondly, it adopts an inclusive and distributed design that ensures equity among all institutions by democratising access to computational resources from the school level to building sustained national capacity. 

Institutionally, NCIMD can be anchored with DST operating in collaboration with CSIR, DBT, and NSM, with a dedicated division managing the programme in mission mode under the guidance of an inter-agency steering committee comprising academia, industry and regulatory representatives. Strategic partnerships with Startup India and Atal Innovation Mission (AIM) would support deeptech translation, while further collaboration with AICTE and UGC would ensure faculty and student training. Engagement with the Confederation of Indian Industry (CII) and the Federation of Indian Chambers of Commerce and Industry (FICCI) would create industry feedback loops and accelerate adoption. Together, this interlinked architecture would enable simulation-guided chemical sciences as a mainstream feature for India’s faster, safer and sustainable research roadmap for technology development at the national scale.

Implementation strategy 

The successful execution of NCIMD requires a phased, scalable and inclusive strategy. Given the diversity of India’s scientific ecosystem – ranging from elite research institutions with state-of-the-art infrastructure to under-resourced colleges in remote regions, the rollout must be ambitious in its vision but grounded in practical constraints. The implementation roadmap can be organised across three key dimensions: infrastructure, institutional coordination and human capacity.

Phased rollout through regional hubs 

NCIMD will adopt a decentralised, hub-and-spoke model anchored in existing academic and national research institutions. The rollout will proceed in three phases:

Phase 1 (years 1–2): Pilot deployment

• Identify 5–7 regional hubs (IITs, IISERs, CSIR labs) to serve as foundational nodes.
• Establish cloud-based access to simulation platforms, leveraging infrastructure under NSM and CDAC.
• Launch seed-funded pilot projects integrating modelling and experimentation in priority areas such as biomass valorisation, green solvents, drug discovery and carbon capture.
• Develop and pilot simulation literacy modules for schools and undergraduate programs in partnership with NCERT and UGC

Phase 2 (years 3-4): National expansion

• Scale up the network to 40–50 institutions, including NITs, state and central universities.
• Deploy standardised training and certification programmes at multiple levels.
• Provide portable simulation toolkits and remote cloud access to institutions lacking local HPC facilities.
• Organise annual simulation challenges and innovation sprints to engage startups, MSMEs and early-stage innovators 

Phase 3 (year 5): Policy integration and sustainability

• Embed simulation requirements into national R&D grant guidelines (DST, DBT, ICMR, CSIR).
• Institutionalise training and practice in simulation approaches within chemistry and materials science curricula nationwide.
• Conduct independent impact assessments and stakeholder consultations to guide the next phase of expansion

Institutional stakeholders and roles 

NCIMD’s success will depend on multi-stakeholder collaboration.  The key roles will include:

• Ministry of Science and Technology: Policy anchor, funding allocation and oversight.
• DST, DBT, CSIR: Technical leadership, platform development and pilot project coordination.
• NSM and CDAC: Computational infrastructure, platform integration and cloud services.
• UGC, AICTE, NCERT: Curriculum reform, faculty training and education pipeline development 
• Startups and industry (via FICCI, CII): Partnerships for application development, internships and innovation challenges.

A central implementation unit within DST will coordinate efforts, supported by an inter-agency steering committee and a technical advisory board comprising computational chemists, educators, industry leaders and regulatory experts.

Addressing barriers and enablers 

To ensure equitable adoption, NCIMD must proactively address foreseeable challenges:

• Infrastructure gaps: Provide subsidised cloud-based computing access and browser-based, lightweight tools for low-bandwidth settings to institutions that lack computing power and reliable internet connectivity. Regional hubs will host shared simulation labs capable of running jobs and offering remote consultation to partner colleges.
• Human capacity: Develop modular training programs with micro-credentials and financial incentives for faculty participation. Create mentorship networks linking premier institutions with regional colleges.
• Institutional resistance: Position simulation as an augmentation and not a replacement of lab work. Implement project-based learning and incentivise the labs that support interdisciplinary research.  
• Funding bottlenecks: Create dedicated NCIMD grant calls that involve collaboration among experimentalists and theoreticians to build a unified platform for integrated learning. Co-finance institutional hardware upgrades with matching grants.

Monitoring, evaluation and feedback

A robust monitoring and evaluation (M&E) framework will be integral to overseeing the functioning of NCIMD. This will include: 

• Annual reviews of participation rates, training completions and simulation–experiment integration outcomes
• Independent audits of infrastructure usage, geographic equity and cost-efficiency
• Stakeholder consultations every 18 months with feedback loops to adjust implementation
• Publication of an annual report tracking metrics, case studies and regulatory adoption

Resource mobilisation 

Initial funding can be drawn from existing schemes under DST, SERB, RUSA and Startup India. Additional support can be sought from CSR contributions (especially from pharmaceutical and chemical companies), multilateral donors and global science philanthropies. In the long term, NCIMD should have a dedicated budget line in the Union Budget and be integrated into the national science, technology and innovation policy roadmap to ensure sustainability. 

Risks and ethics 

While simulation-guided chemistry holds transformative potential for accelerating innovation and strengthening regulatory foresight, it also introduces new layers of risk and ethical complexity. 

These risks span technical, institutional and societal dimensions and must be addressed deliberately within the design of the NCIMD framework to ensure safe, equitable and trustworthy outcomes. As modelling tools become more powerful and accessible, there is a risk that simulations will be treated as definitive rather than as predictive heuristics. This could lead to false confidence in unverified results, potentially resulting in unsafe products, ineffective drugs or flawed materials entering the innovation pipeline. 

A second challenge lies in the opacity and potential bias of AI-driven molecular design platforms. With increasing use of machine learning algorithms in tasks such as retrosynthetic planning, toxicity prediction and molecule generation, there is a need to ensure that the training sets are not incomplete, proprietary or biased. If these tools are used to guide regulatory decisions or public health interventions, their outputs should be explainable, reproducible and auditable. Failure to address these issues could reinforce systemic bias, generate flawed predictions that are difficult to contest or replicate. The NCIMD framework must therefore preserve the primacy of experimentation as a critical counterpart to simulation, particularly in safety-sensitive domains such as pharmaceuticals, food chemistry and environmental applications. 

These technologies also carry dual-use concerns. The same computational tools that can design life-saving drugs or sustainable catalysts can also be used to generate toxic agents, chemical weapons precursors or environmentally hazardous materials. The distributed and digital nature of simulation platforms makes monitoring and enforcement challenging, necessitating strong governance and responsible access controls. Ethical considerations extend to intellectual property, access and equity. Without careful design, simulation resources could remain concentrated, marginalising under-resourced colleges and researchers. Additionally, the ownership of AI-generated compounds raises unresolved questions about rights, attribution and benefit-sharing. 

To mitigate these risks, the Foresight and Ethics unit within NCIMD should lead the development of the ethical frameworks, review protocols and safeguards. Recommended actions include:

• Establishing transparent audit and verification mechanisms for simulation tools used in regulatory or commercial decision-making.
• Developing ethical usage guidelines for dual-use modeling platforms, with institutional oversight
• Advocating open-source standards and documentation requirements, and reproducibility protocols for AI-based chemistry tools

By embedding these safeguards into NCIMD from the outset, India can not only accelerate simulation and enable innovation but also demonstrate global leadership in responsible technology governance, ensuring that research advances in chemical sciences are safe, equitable and aligned with long-term public interest. 

Conclusions

India stands at a pivotal juncture in its scientific and technological trajectory. As chemistry-driven innovations become central to solving grand challenges, ranging from clean energy transitions and sustainable agriculture to affordable healthcare and materials security, there is a compelling need to modernise how the research is conceived, executed, scaled and governed. The integration of computational modelling with experimental chemistry is a strategic necessity for accelerating discovery, reducing failure rates, using resources more efficiently and enhancing national capacity for foresight. The proposed NCIMD offers a comprehensive, future-oriented policy framework to institutionalise simulation-guided research across India’s scientific ecosystem. By combining democratised infrastructure, inclusive capacity-building, school-to-startup education pathways and anticipatory governance, NCIMD charts a pathway for scientific excellence with social and regulatory readiness. 

What sets this initiative apart is its integrated approach, linking public infrastructure, curriculum reform, students, researchers, experimentalists, theoreticians and industrialists under a coordinated national mission. It ensures that advanced tools such as quantum chemistry simulations or AI-driven molecular design become accessible to a broader and more diverse research community. Most importantly, the NCIMD lays the foundation for a future-ready workforce equipped to thrive in an interdisciplinary, digital-first scientific environment. By turning today’s fragmented research efforts into a nationally coordinated, simulation-enabled ecosystem, India has the chance to convert its scientific potential into global leadership,  delivering innovations that are safer, sustainable, more inclusive and truly transformative for society.