Blockchain-enabled Drug SCM in Pharmacy: A Review of Integration with IoT and ERP Systems

Why “Blockchain + IoT + ERP” is becoming central to drug SCM

Pharmaceutical supply chains are unusually sensitive compared with most consumer-goods networks because they must maintain product authenticity, patient safety, and regulated traceability—often at unit or pack level—across many independent trading partners (manufacturers, 3PLs, wholesalers, dispensers/pharmacies, and regulators). At the same time, modern supply chains are more global, more outsourced, and more digitally fragmented than ever. These characteristics create persistent risks: counterfeit or substandard medicines entering distribution channels, temperature excursions in cold-chain products, diversion into gray markets, and slow recall/returns cycles due to poor end-to-end visibility. The World Health Organization has long highlighted the magnitude of the quality problem, estimating that in low- and middle-income countries about 1 in 10 medical products can be substandard or falsified, which directly motivates stronger track-and-trace and verification systems. World Health Organization+1

 

Traditional information systems in pharma SCM are dominated by (i) ERP as the system of record for procurement, manufacturing, inventory, quality, finance, and compliance; and (ii) partner-facing track-and-trace, warehouse management (WMS), and transportation management (TMS) systems. However, even with mature ERP deployments, multi-party traceability breaks down because each partner maintains its own database, reconciles transactions through bilateral messages, and interprets events differently. This often results in delayed dispute resolution (e.g., mismatch between shipped vs received serial numbers), manual exception handling, and weak transparency when multiple intermediaries are involved. To bridge these gaps, regulators have pushed the industry toward interoperable electronic tracing. In the United States, the FDA’s Drug Supply Chain Security Act (DSCSA) establishes a framework to achieve electronic, interoperable identification and tracing of certain prescription drugs at package level, and the FDA has published multiple guidance documents and compliance policies to support implementation.

 

U.S. Food and Drug Administration+2U.S. Food and Drug Administration+2

Against this backdrop, blockchain is increasingly examined as a shared “trust fabric” for multi-organization networks: an immutable ledger, smart-contract workflow, and auditable event history that can reduce reconciliation effort and improve non-repudiation of supply chain events. But blockchain alone is not sufficient: (a) drug SCM requires physical-world sensing (temperature, humidity, shock, geolocation), which is best provided by IoT; and (b) it requires operational execution and compliance controls, which largely remain in ERP and related enterprise applications. Hence, the realistic path is not “replace ERP with blockchain,” but “integrate blockchain with ERP and IoT so that each layer does what it is best at.” This review therefore focuses on integration design: how data flows from IoT devices into standardized event models, how ERP processes invoke blockchain transactions, how permissions and privacy are enforced, and how such systems meet regulatory traceability requirements while remaining scalable and cost-effective.

 

A key motivation for integration is the accelerating importance of cold-chain and specialty medicines (biologics, vaccines, cell & gene therapies). Market analyses show strong growth in pharma cold-chain logistics/packaging segments, reflecting the rising operational need for validated temperature control and traceability across distribution. Grand View Research+1 When product value is high and spoilage risk is significant, end-to-end monitoring and rapid exception handling become essential. IoT sensors provide evidence of environmental conditions, ERP governs quality release and quarantine decisions, and blockchain provides a tamper-evident, shared record across partners. In this sense, blockchain-enabled drug SCM is best understood as a socio-technical system linking regulated processes, enterprise records, and physical telemetry into a coherent, auditable data chain.

 

2. Foundations: Drug SCM processes, standards, and regulatory drivers

Drug supply chain management (SCM) in pharmacy settings spans upstream serialization and aggregation, logistics handoffs, verification at dispensing, and downstream returns and recalls. The operational reality is that different participants experience the supply chain through different “truths”: manufacturers emphasize batch genealogy and release; 3PLs emphasize handling and lane performance; wholesalers emphasize inventory velocity and ownership changes; pharmacies emphasize inbound verification, dispensing, and returns; and regulators emphasize traceability and suspect product investigation. A functional integration architecture must therefore align with both process and data semantics, not merely move messages between systems.

 

Regulatory traceability is a primary driver for digitization. The FDA describes DSCSA as outlining steps to achieve an interoperable, electronic way to identify and trace certain prescription drugs, supporting detection and removal of harmful or illegitimate products. U.S. Food and Drug Administration The implementation reality has required staged timelines and “stabilization” policies to help trading partners mature interoperable systems—illustrating that interoperability is as much organizational and standards-driven as it is technical. U.S. Food and Drug Administration+1 Importantly, DSCSA does not mandate blockchain; it mandates secure, interoperable electronic exchange. This leaves room for blockchain networks, EPCIS-based event exchange, or hybrid architectures, as long as they achieve compliance outcomes.

 

A widely used approach to interoperability in product event data is the GS1 EPCIS (Electronic Product Code Information Services) standard, which defines how supply chain “events” (commissioning, packing, shipping, receiving, etc.) are represented and shared. GS1 positions EPCIS as enabling real-time sharing of information about the whereabouts and status of products across partners, and EPCIS 2.0 extends capability for modern traceability use cases. GS1+1 In practical terms, EPCIS helps ensure that a “shipping event” has consistent meaning regardless of which partner publishes it. This matters because blockchain ledgers are only useful when the events written to them are semantically consistent and verifiable.

 

From an enterprise perspective, ERP (e.g., SAP, Oracle) governs master data (materials, batches, suppliers), transactional data (purchase orders, goods receipts, invoices), and compliance records (quality inspections, deviations, CAPA). ERP is optimized for internal control and financial truth, not for cross-enterprise shared truth. Therefore, integration commonly uses middleware (ESB/iPaaS), API gateways, and event streaming to connect ERP with WMS/TMS/serialization platforms. Blockchain networks, when introduced, should integrate into this existing enterprise integration ecosystem rather than bypass it. A practical principle is: ERP remains the system of record, while blockchain becomes a system of shared verification and cross-party audit.

 

IoT introduces another dimension: real-time telemetry from sensors attached to pallets, boxes, or vehicles; RFID and QR scans; smart locks; and environmental monitoring within warehouses or cold rooms. IoT data is high-volume and noisy, whereas blockchain storage is comparatively expensive and capacity-limited. Hence, modern designs typically store raw telemetry off-chain (data lakes, time-series databases) and commit only hashes, summaries, or exception proofs on-chain. This is reinforced by research proposing hybrid architectures where blockchain ensures integrity and auditability while off-chain systems handle bulk data and analytics. ScienceDirect+1

 

To structure integration thinking, it is helpful to decompose drug SCM into layers:

(a) Physical layer: items, packs, cases, pallets; cold-chain equipment; vehicles; warehouses.

(b) Sensing layer: RFID/QR scans; temperature/humidity sensors; GPS; shock sensors.

(c) Enterprise layer: ERP/WMS/TMS/serialization; quality systems.

(d) Inter-organizational layer: standards-based event exchange (EPCIS), EDI/API, regulator reporting.

(e) Trust layer: blockchain ledger + smart contracts + permissioning + audit.

Blockchain-enabled SCM emerges when the trust layer is tightly coupled with standardized event exchange and enterprise execution. In pharma, the trust layer must also support privacy, because trading partners may not want to reveal commercial quantities or relationships. Permissioned blockchains (e.g., Hyperledger Fabric) are therefore frequently proposed for supply chains, offering membership control and channel-based privacy. ScienceDirect+1 This foundation sets the stage for deeper discussion of architectures and integration patterns.

 

3. Blockchain architectures for drug traceability: design patterns and platform choices

Blockchain systems vary widely in governance, throughput, privacy, and cost. In drug SCM, most practical proposals converge on permissioned (consortium) blockchain rather than public, fully open networks. The core reason is that pharmaceutical traceability requires controlled participation (licensed manufacturers, accredited distributors, registered pharmacies) and contractual obligations around data handling. Permissioned systems also provide stronger identity management and can support selective disclosure, which is crucial when commercial data is sensitive.

 

3.1 Common architectural patterns

A useful way to classify designs is by how they handle (i) traceability events, (ii) document exchange, and (iii) privacy.

Pattern A: On-chain event ledger (minimal documents).

Partners write standardized events (commission, ship, receive) to the ledger, and the ledger is the shared truth. In practice, events are often EPCIS-like, but represented as blockchain transactions. This maximizes auditability but can stress performance at scale if every scan becomes a transaction.

 

Pattern B: Hybrid ledger + off-chain EPCIS repository.

Partners keep EPCIS repositories off-chain (or in shared cloud), exchange events via EPCIS interfaces, and the blockchain stores hash commitments or pointers to event batches. This pattern reduces chain load and supports standard interoperability, aligning with research that combines blockchain with off-chain EPCIS services. MDPI

 

Pattern C: Smart-contract workflow for ownership/verification.

Here, blockchain smart contracts enforce state transitions: a serialized unit cannot be dispensed unless it has a valid chain of custody; returns require verification; suspect product triggers an investigation workflow. This supports DSCSA-like verification and exception handling. The FDA has also explored blockchain interoperability through pilot reporting, indicating industry interest in using blockchain concepts to address interoperability challenges. U.S. Food and Drug Administration

 

3.2 Platform considerations (Hyperledger Fabric, Sawtooth, Ethereum-based)

Research and prototypes often feature Hyperledger Fabric for supply chains because it is permissioned, modular, and supports private channels and pluggable consensus. Work on pharma SCM has compared Hyperledger Fabric and Sawtooth in terms of resource utilization and suitability for decentralized applications, suggesting that platform choice affects scalability and operational costs. ScienceDirect Other studies use Ethereum smart contracts to orchestrate pharmaceutical transactions in decentralized marketplaces, demonstrating the programmability of public-chain tooling, but public chains introduce transparency and fee challenges not always desirable in regulated SCM. ScienceDirect.

 

3.3 Governance and consortium operating model

Blockchain’s technical capability does not guarantee adoption; governance defines who can write, read, and validate data, and how disputes are handled. A consortium model typically defines:

1.           Membership criteria (licensing, audits, onboarding KYC)

2.           Data sharing rules (what events are shared, at what granularity)

3.           Liability and dispute resolution procedures

4.           Cost-sharing model (nodes, hosting, onboarding, transaction costs)

5.           Change management and upgrade process

In pharma networks, governance must align with regulatory obligations and business confidentiality. For example, a dispenser may need to verify a product’s legitimacy without learning the wholesaler’s upstream pricing or other commercial relationships. Fabric’s private channels, or application-layer encryption with selective disclosure, can support such needs, but they complicate integration and standard compliance.

 

3.4 Practical data model: what actually goes on-chain?

A typical minimal on-chain record for a serialized drug unit or aggregated case includes:

6.           Product identifier (GTIN/NDC mapping), serial number, batch/lot, expiry

7.           Event type and timestamp (commission, pack, ship, receive, dispense, return)

8.           Location or GLN (as allowed), and business step/disposition

9.           Digital signatures of event publisher and validator

10.         Hash pointer to off-chain documents (invoice, pedigree, sensor logs)

This “minimum viable ledger” approach helps keep the blockchain lean while preserving auditability. It aligns with the reality that IoT telemetry and PDFs (certificates, shipping docs) are too heavy for direct on-chain storage.

 

 

 

 

 

 

 

DISCUSSION

7.6 Methodological notes for publication quality

For a review paper, you can strengthen scientific rigor by:

Providing a PRISMA-like selection narrative (databases searched, keywords, inclusion/exclusion)

Classifying studies by architecture type (permissioned vs public; on-chain vs hybrid)

Comparing performance metrics reported (TPS, latency, storage)

Highlighting evidence gaps (few real deployments; limited cost models; privacy tradeoffs)

In summary, evaluation should connect the public health and operational drivers (counterfeit risk and cold-chain growth) to measurable KPIs and implementation evidence. This elevates the paper from “technology advocacy” to a structured, evidence-driven review.

 

8. Challenges, research gap Etc

Despite strong conceptual fit, blockchain-enabled drug SCM faces technical, organizational, and regulatory hurdles. A scopus-level review must explicitly discuss these limitations and propose research directions that are both feasible and impactful.

 

8.1 Scalability and performance at serialization scale

Pharma traceability can involve billions of serialized units annually across large markets. Writing every scan event on-chain is rarely viable. Even permissioned networks can face throughput and storage constraints when naïvely designed. Therefore, future architectures should emphasize:

Aggregation (unit→case→pallet) with selective unit-level anchoring

Batching of events (e.g., per shipment or per time window)

Off-chain event repositories with on-chain hashing (hybrid EPCIS approach) MDPI

Event streaming pipelines feeding both analytics and ledger anchoring ScienceDirect

A key open question is “how much on-chain is enough” to deliver non-repudiation without overwhelming infrastructure.

 

 

8.2 Interoperability fragmentation

Even when EPCIS is available, implementations vary; different partners interpret business steps and dispositions differently. The DSCSA push for interoperable exchange highlights that standard conformance testing and shared governance are essential. U.S. Food and Drug Administration+1

 

Future work should propose:

Reference conformance suites for EPCIS event quality

Canonical traceability profiles for pharmacy workflows (receive/dispense/return)

Cross-network interoperability (multiple blockchains or mixed tech stacks)

The FDA’s exploration of blockchain interoperability concepts suggests that interoperability is an active area of experimentation, not a solved problem. U.S. Food and Drug Administration

 

8.3 Privacy, competition, and data ownership

Supply chains are competitive networks. Trading partners may resist sharing data that reveals volumes, routes, or relationships. Permissioned platforms help, but privacy-preserving analytics and selective disclosure remain challenging. Likely future directions include:

Policy-based encryption and key management aligned with roles

Private data collections and “need-to-know” channels

Auditable access logs to satisfy compliance audits

Research on privacy-preserving proofs for authenticity assertions (emerging)

 

8.4 IoT trust and the “oracle problem”

IoT devices are the oracles that connect physical reality to digital records. If devices are compromised, blockchain immutability preserves falsehoods permanently. Hence, research should emphasize:

Secure hardware provisioning and attestation

Sensor redundancy and anomaly detection

Cross-validation with logistics milestones (scan events vs GPS routes)

Human-in-the-loop quality release in high-stakes exceptions

 

8.5 Organizational adoption and cost

A recurring barrier is cost vs perceived benefit. Sensors, integration development, node hosting, and governance overhead can be significant, especially for smaller pharmacies. Adoption strategies that may improve feasibility:

Start with high-value/high-risk segments (cold-chain biologics, controlled substances)

Use shared service models (managed blockchain nodes, managed EPCIS repositories)

Provide incremental benefits (reduced chargebacks, faster receiving) before full transformation

Align incentives via consortium agreements and regulatory readiness programs

The pharmaceutical supply chain operates within one of the most highly regulated and risk-sensitive industrial environments, where failures in traceability, product integrity, or cold-chain compliance can directly affect patient safety and public health. This review has examined blockchain-enabled drug supply chain management (SCM) in pharmacy contexts, with a particular emphasis on its integration with Internet of Things (IoT) technologies and enterprise resource planning (ERP) systems. The synthesis demonstrates that blockchain’s value does not lie in replacing existing enterprise infrastructure, but rather in acting as a shared trust and verification layer that enhances transparency, accountability, and coordination across organizational boundaries.

 

A key insight emerging from this review is that integration is the critical success factor. IoT devices provide real-time, physical-world evidence of drug handling conditions such as temperature, humidity, location, and tampering, which is especially vital for cold-chain pharmaceuticals and high-value biologics. However, IoT data alone lacks institutional trust when shared across multiple stakeholders. By anchoring cryptographic proofs and exception summaries on a permissioned blockchain, the integrity and non-repudiation of these physical events can be ensured without overwhelming the ledger with high-volume sensor data. This hybrid on-chain/off-chain approach offers a practical balance between scalability and auditability.

 

ERP systems remain central to pharmaceutical operations, governing inventory management, quality assurance, regulatory compliance, and financial reconciliation. The review highlights that blockchain-enabled SCM architectures are most effective when ERP systems retain their role as systems of record, while blockchain networks function as systems of shared verification. Event-driven, asynchronous integration patterns allow ERP processes—such as goods receipt, authenticity verification, quarantine, release, and recall—to interact with blockchain networks without compromising enterprise performance or availability. This architectural separation reduces organizational resistance and aligns with existing regulatory expectations.

 

Interoperability is another dominant theme addressed in this paper. Standards such as GS1 EPCIS provide a common semantic foundation for representing supply chain events, enabling consistent interpretation across diverse partners. Blockchain networks that align with EPCIS-style event models—or that anchor off-chain EPCIS repositories—are better positioned to support regulatory frameworks such as the Drug Supply Chain Security Act (DSCSA), which emphasizes interoperable electronic tracing rather than specific technologies. The inclusion of interoperability gateways ensures that partial adoption does not fragment the ecosystem and allows gradual onboarding of pharmacies, distributors, and manufacturers.

 

Despite its promise, blockchain-enabled drug SCM faces persistent challenges. Scalability at serialization-level volumes, data privacy in competitive supply networks, governance of multi-stakeholder consortia, and the security of IoT “oracles” remain open research and implementation concerns. Smaller pharmacies may also face cost and capability barriers, underscoring the need for shared-service models and targeted deployment strategies focusing initially on high-risk or high-value product segments. Future research should prioritize large-scale empirical pilots, standardized conformance testing for traceability events, and privacy-preserving verification mechanisms that satisfy both regulators and commercial stakeholders.

 

In conclusion, blockchain-enabled drug supply chain management—when tightly integrated with IoT sensing and ERP-based execution—offers a compelling pathway toward more transparent, resilient, and trustworthy pharmaceutical distribution systems. Its true impact will be realized not through isolated pilots, but through standards-aligned, governance-backed, and economically sustainable deployments that address real operational and regulatory needs within pharmacy ecosystems.

 

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