Identifying a promising drug, its development, clinical trial, and its commercialization is a herculean task indeed. It takes years together and a huge amount of investment for a single drug to make available in the market.
Artificial Intelligence, Blockchain, and Big Data together influences the drug development process, its delivery, and thus cuts down the drug pricing.
Let us investigate how.
Blockchain, Big Data, and Artificial Intelligence are the three buzzwords in the techno-town creating revolution with a promising future in almost all industries invariably.
The pharmaceutical industry is one, where the advances in technology would help to add value to the drug supply chain, research, cost cuttings, personalized patient treatment, and, etc.
Before that, let us understand why medicines and drugs are costly?
Pharmaceutical companies readily invest billions of dollars in drugs. And, bringing these medications to the market and patients also entails the cost.
Further, the cost of drug development is also increasing the scale. It is noted that the average time for a drug to be developed and released into the market is about 15 years. The identification of a promising drug is challenging which engulfs about 4-5 years, and the remaining years for clinical trials and commercialization. Evidently, the R&D cost and commercialized molecular entities in a year do not match at all.
Moreover, the supply chains are insecure and complex, making the things further complicated. The ecosystem comprises a network of suppliers and logisticians. And, safety must be ensured by adhering to strict regulations and practices to avoid drug contamination.
Henceforth, the companies invest in RFID [Radio frequency identification], chromatography, holographic labels, and, so forth.
Unfortunately and obviously, the costs are passed on to the consumers. At this juncture, the implementation of advanced technologies holds a promising future in cutting the costs and bring down the drug prices.
Blockchain in Pharmacy:
- Blockchain has the ability to provide a decentralized, transparent, and immutable record keeping for tracing the drugs across the supply chain. A secure and trackable supply chain leads to fewer chances of counterfeiting, cut down the associated costs, and thus safer and cheaper medicine.
- It serves as a platform to share electronic health records between the organizations and research center, which speeds up the drug development process.
- It also helps in the speedier medical billing process.
Big Data in Pharmacy:
- The data collected through clinical trials are easily received by the researchers and managed for further contribution in the research at the earliest phase.
- With the help of “smart contract”, the researchers are able to collect real-time data during a patient treatment.
- The patients receive payment for participation in the research.
- Big data is also used to reveal drug abuse, analyze patient’s prescription refill frequency, and any other user-related data.
- The data capture at all stages influences the efficiency of drug development which cuts down the drug development cost.
Artificial Intelligence in Pharmacy:
It is stated that “Orion Health's Amadeus Intelligence will use machine learning models initially to predict patient costs and readmission risks, analyze clinical and financial outliers and enable accurate diagnosis coding and quality metric reporting to improve decision making at the point of care and target resources which will result in significant cost savings."
Artificial Intelligence is able to learn and discover the things at a faster rate and this knowledge could be utilized in the drug development process.
The AI programs have a marvelous increasing capacity to analyze the big data, identify the patterns, and generate the algorithms. These programs help the researchers to generate the hypotheses at a faster rate and make the drug discovery process effective and less expensive.
“One of the most widespread uses is for repurposing drugs — finding new uses for existing drugs or late-stage drug candidates. “You don’t have to repeat all the phase I testing and all the toxicology testing when you take it into another phase II trial [for] a different indication, so you can accelerate the process of medicine development quite dramatically,” explains Jackie Hunter, chief executive officer of Benevolent AI, Europe’s largest AI start-up to date.
In addition, AI analyzes the database of the electronic medical records, public health data to identify the hidden patterns leading to the potentiality of the molecular targets for a disease.
In brief, applying AI algorithms would help the researchers to quicken the drug development process influenced by the availability of clinical trial results, repurposing of drugs, and market penetration.
Key Takeaways from the Discussion:
Currently, more than 100 companies including Amazon, Google, IBM Watson and other tech-giants are investing in AI algorithms successfully.
By witnessing the advances in the varied industries, there is no doubt that these 3 breakthrough technologies would hold a promising future in cutting down the costs of the drug and make it available for all the needed patients at an economic rate leading to a better health and survival.
A simple cutline in the timeline of drug research, production and its delivery influenced by the advanced technologies wins the show and brings cost-effective medical care.
