Specialty products in the pharma industry

Mar 15, 2024 | Commercial Analytics
Shrikant Mani Bhaskar
Specialty Pharma

Specialty products in the pharma industry

Specialty products in the pharma industry 1024 506 deepak

In the recent years, there has been a lot of investment into research and development of Specialty products in the pharma industry, Specialty Drugs are highly specific, generally more effective, but significantly costlier to produce. However, though they are small volume, they are very high profit segment for Pharma companies. Hence, specialty Drugs play a pivotal role in the growth of the company.

Characteristics of specialty pharmaceuticals:

  1. High Cost:
  2. Tend to be much more expensive drug than traditional drugs. Although they account for less than 2% by volume of total prescriptions in the US, they account for around 51% of the total spending.

  3. Administration:
  4. Usually, they require special administration methods such as injections, infusions, or other methods.

  5. Monitoring and support:
  6. Most often, patients taking specialty drugs need special attention from the healthcare professional.

  7. Unique Supply Chain and Storage:
  8. Specialty drugs are biological compounds with short shelf-life, generally requiring special shipping and storage conditions such as cold supply chain.

  9. Unique Distribution:
  10. Owing to relatively high prices, specialty products are consumed in low volumes. There are roughly 3200 Specialty Pharmacies in the US, covering all specialty products.

  11. High utilization of Hub and Patient Assistance Programs:
  12. Owing to high costs and the complex distribution model, Specialty Pharma companies leverage a lot on Patient Hubs and Patient Assistance Programs.

Data Challenges in Specialty Pharma:

  1. Data Procurement: Data collected at the hub and specialty pharma has a big difference in terms of volume and information. Mostly specialty pharma collects a huge amount of data and does not send it back to hub. Hub also does not want to store that data as larger amounts of data require a team and infrastructure which comes up with the cost.

  2. Lack of Data Standards: Specialty Pharma companies have to rely on Specialty Distributors to maintain accuracy of data. Especially in terms of entity names, providing the right HIN, HIBBC, DEA Numbers or other identifiers that help in mastering the data. The same standards need to be complied with by the Hub. This is not often the case.

  3. Data Lags: There are multiple lags in the whole data collection process viz.

    • delay in time between shipment and inventory data reported back from Specialty Distributor.
    • Delay between time the drug is shipped from Specialty Distributor to Specialty Pharmacy and the time when the drug is sold by the Specialty Pharmacy. Only once this drug is sold will the Specialty Pharmacy report back the same in the inventory data.
    • Time gap between Hub reporting data about a patient to the actual sale happening.
    • Identifying duplicate reporting between Specialty Distributor, Specialty Pharmacy and Hub. Over reporting has ramifications on goal attainment and incentive compensation leading to potential financial losses to Pharma Companies
    • Identifying duplicates in Chargebacks, which could also lead to financial losses to the company.

Poor data quality results in financial losses to companies directly and indirectly by means of time loss in identifying issues, rework and misreporting.

Addressing Data Quality Challenges:

The Specialty market is pegged to grow to ~ 1,500 Bn USD by 2033, from the current 68.3 Bn in 2023. With rapid and explosive growth, Specialty Pharma Companies need to quickly formulate a strong data quality and governance strategy, augmented with the right platforms and accelerators. Pharma companies have tried to adopt the governance and data quality strategy leveraged for retail products, but this has not yielded much success. The data challenges are very different between retail and specialty products. Configuring a DQ platform for specialty data is a very resource intensive process as well as requiring a high level of business knowledge. Moreover, the data quality challenges are constantly changing, which requires Specialty Pharma companies to adopt a dynamic, smart, purpose-built solution to data quality.

Resolution to data quality issues in Specialty Pharma:

  1. A robust Master data management (MDM) process is needed to remove data duplicity and maintain unique records for the HCP and HCO involved in the process.

  2. Each NPI record should be checked with the Government maintained NPI Registry database so that any invalid NPI will be rejected or again asked to check from the data steward. This will lead to accurate reporting.

  3. A flexible and dynamic Data Model should be followed to accommodate the changing layouts of Specialty Pharmacies.

  4. Generalization of Business rules across Specialty Pharmacies and IT team processing the data for accurate reporting and business insights.

  5. A Data Quality framework must be implemented to address basic issues in Data like NULLS, Missing values, partial data etc.

  6. A Data Quality Framework and platform that can identify data quality issues specific to Specialty data.

  7. A smart and dynamic framework that can evolve as the data quality issues evolve with growing business


In summary, the specialty pharma sector, focusing on tailored drugs for specific medical conditions, heavily relies on accurate and reliable data. Despite facing challenges, particularly in data quality, the industry can enhance its capabilities by implementing robust processes and methodologies. By overcoming these challenges, specialty pharma companies can ensure accurate and reliable data, supporting their success in research, compliance, and overall business operations.

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