Though the cryptocurrency side of blockchain technology has dominated news headlines in the last year, the technology has real promise in biotechnology and the life sciences. A recent survey (September 2018) by the Pistoia Alliance found that 60% of professionals in the pharmaceutical and life sciences industries were using or experimenting with blockchain technologies in 2018, as compared with 22% in 2017.

Blockchain technology provides three key capabilities1 that are missing but required for the life sciences sector to evolve to the next level:

  • Ultra-secure and immutable storage of information
  • Decentralization and increased transparency of transactions
  • Incentivization of key stakeholders

Key use cases for blockchain in biotechnology include:

  • Battling counterfeit drugs
  • Enhancing virtual clinical trials
  • Efficient 3D printing of drugs

These issues are ordered according to the likely adoption timeline for the use case.

Battling counterfeit drugs

Pharmaceutical companies spend billions of dollars and go through an arduous process to produce and commercialize prescription drugs. With the global counterfeit drug market valued at $200 billion2 annually, there is a clear motivation in the pharmaceutical sector to fight counterfeiting. What is also at stake are human lives. Adverse reactions and effects due to fake drugs can lead to death.

In emerging markets, 10–30% of prescription drugs2 are typically counterfeit, with issues ranging from drugs with incorrect ingredients to incorrect proportions of ingredients. Most of the counterfeit drugs are being produced outside the United States and sold worldwide. Antibiotics and antimalarials are two of the drug categories most commonly counterfeited, yet many classes of drugs purchased online are at risk and account for nearly 40% of all counterfeits. Counterfeit drugs are also growing in the United States with the explosion of the opioid crisis. Recent reports have indicated that fake opioids laced with fentanyl have caused deaths in 12 U.S. states.3

It is for this reason that key members of the pharmaceutical industry started the MediLedger4 blockchain project in 2017. The MediLedger project is focused on providing “track and trace” capability to players in the pharmaceutical supply chain. It includes teams from Genentech, AmerisourceBergen, McKesson, Pfizer, and AbbVie. Initial pilots are positive and suggest that a blockchain-based solution will enable compliance with the Drug Supply Chain Security Act (DSCSA) while improving operations and reducing the supply of counterfeit drugs.

Lack of supply chain transparency and product authenticity are at the root of global pharmaceutical fraud. Without transparency in the supply chain, it is very difficult to pinpoint the origin of the fraud, identify the bad actors who perpetrated the crime, or verify product authenticity. What is needed is for the entire process, from production to quality assurance to distribution, to be secured in an unhackable database with each entry cryptographically signed and encrypted. Blockchain technology clearly provides these capabilities and the resulting transparency.

Enhanced virtual clinical trials

Clinical trials are very expensive, laborious, and inefficient parts of drug development. According to the Journal of American Medicine (JAMA), rising clinical trial expenses are a serious concern for pharmaceutical companies, with costs ranging from tens of millions to hundreds of millions of dollars. These high costs are due to the difficulty of identifying and recruiting qualified participants, coping with high attrition rates (30%+), and managing and administering an in-person process across thousands of participants for an extended period.

Administering the in-person process drives up costs due to the need to hire qualified full-time medical staff and recruit participants from a localized region with access to specific clinical trial facilities. Currently, a clinical trial visit costs on average $3000–7000, and participants need to visit the facility 12–24 times per year. This geographic restriction limits the size and demographics of the participant pool, and the frequent office visits create retention issues. Virtual clinical trials can broaden the participant pool, reduce the need for full-time medical staff, and increase retention by providing a patient-centric experience. Pharmaceutical companies such as Pfizer, Merck, Sanofi, GlaxoSmithKline, AOBiome, and Novartis have implemented virtual approaches, particularly in non-intervention clinical trials, with mixed results.5

Results have been mixed for a variety of reasons including data reliability and integrity issues, substandard compliance, data security and privacy issues, and poor consent management. Blockchain technology in combination with wearables and Internet of Things–based sensors can provide the correct mix of data integrity, data security, and data privacy required by U.S. Food and Drug Administration (FDA) regulations and the Health Insurance Portability and Accountability Act (HIPAA).

Blockchain solutions also provide smart contract technology to automatically ensure patient consent data is logged, digitally signed, and fully auditable. Tokenized rewards, rather than current monetary incentives, could be provided to participants to improve compliance, increase engagement and loyalty, and create a much more patient-centric experience.

Participant identification and recruitment could be significantly streamlined if historical medical data were accessible via a blockchain-based personal health record (PHR). This type of PHR can assure stakeholders that their data will be protected without compromising privacy and confidentiality of sensitive patient health data.

With broader adoption of blockchain-based PHRs, pharmaceutical companies could scan populations worldwide to quickly find the right set of diverse patients from global populations. Blockchain technology can create the right trust layer for patient data, dramatically increasing data shareability globally and greatly reducing the costs, complexity, and burden of clinical trials.

Efficient 3D printing of drugs

In 2015, the FDA approved the first 3D-printed drug, Spritam®, for epilepsy. In late 2017, the FDA also provided guidance6 on the use of 3D printing for personalized drugs that can be printed in nontraditional manufacturing facilities, like a hospital or doctor’s office. For 3D printing to become an efficient engine for manufacturing on-demand personalized medicine, however, there must be a huge leap forward in the handling of patient data.

The ability to deliver personalized medicine is directly related to the amount and quality of the patient medical data available, as well as data about people like the patient. Patient data—specifically “omics” data (such as genomics, epigenomics, proteomics, and metabolomics data) as well as the patient’s microbiome and allergy profile—are critical for selecting the right types and dosages of medication for a particular symptom set. Longitudinal population health data is also important for understanding the range of potential outcomes from different medications considering the patient’s age, gender, ethnicity, and other factors.

According to industry surveys, as blockchain technology gains currency in the life sciences and healthcare, it could shorten development cycles, promote medical record centralization, improve network coordination, clarify drug traceability, and enhance the consistency of clinical trial processes. [LeoWolfert / Getty Images]
Today, unfortunately, gaining access to these specific types of data for a particular patient is difficult because data is fragmented and siloed across many providers. Centralized systems have not proven effective because data stored with many patient records present a single point of failure and a rich payoff to hackers. A blockchain-based PHR keyed to a person’s biometrics, however, could enable such a foundation, and an immutable blockchain ledger for logging transactions would minimize data tampering. In a similar way, blockchain technology can enable longitudinal data to be shared, creating useful datasets across many different population pools.

With such a foundation, it becomes possible to run artificial intelligence (AI)- and machine learning (ML)-based systems on the data to rapidly determine the best types of medicine and active ingredient dosages personalized to the patient’s needs. When AI/ML output is integrated with a 3D drug printer, a patient’s personalized medication could be printed at a doctor’s office or pharmacy.


Blockchain technology has tremendous potential to reduce drug counterfeiting, greatly improve the cost-effectiveness of virtual clinical trials, and usher in a new era of personalized medicine. Many other use cases are possible, and the early adopters will develop a significant competitive advantage over those that will follow.



Jordan Woods and Radhika Iyengar-Emens


Jorden Woods is managing partner and Radhika Iyengar-Emens is managing partner and founder at DoubleNova Group.

Previous articleCatalent Invests $200M in Fast-Growing Biologics Manufacturing Business
Next articleShort Stories to Peruse—With Info You Might Use…