$2.6B to create a prescription drug? Something has to change
Next time you see an advertisement with a narrator talking about a new prescription drug while a slow-moving video shows people enjoying life free from pain or discomfort, remember this: $2.6 billion. That’s what it cost the pharmaceutical company to develop the drug before it was approved for marketing.
This estimate is from a 2016 study by Tufts Center for the Study of Drug Development based on a 2013 survey of 10 pharmaceutical firms’ research and development costs for 106 new drugs.
Of the $2.6 billion, the cost to develop a compound approved by the U.S. Food and Drug Administration (FDA) is $1.4 billion, but it takes $1.2 billion to develop compounds that were abandoned in the testing phase, along with expected returns investors had to forego until the development process was complete.
The full product lifecycle of a new drug is close to $3 billion when adding in post-approval research and development costs, along with the cost of testing new formulations, dosage strength and monitoring patient safety and long-term side effects.
Compared to the previous decade (1993 to 2003), the study found development costs increased by 145% (approximately $1 billion per approved drug). The good news is that the average time it takes for drugs to be approved is decreasing. But so is the failure rate. Only 12 percent of drug compounds (about one out of 8.5) brought to clinical trial make it across the finish line to receive FDA approval.
Bringing drugs to trial
Clinical trials are the primary way for researchers to know if a new drug provides a safe and effective treatment for certain medical conditions. The study noted the cost of trials is increasing due to complexity, however. This often results from trial sizes getting larger and higher cost for inputs from the medical sector.
Pharmaceutical manufacturers are starting to use artificial intelligence (AI) to speed research and enable faster and more accurate clinical trials. The technology is being applied during the discovery and research phase to analyze complex sets of data to generate and test new hypotheses.
Machine learning is the most common form of AI that is being used by pharmaceutical companies to analyze data from various sources that include electronic medical record systems, DNA repositories and real-time data from health and fitness apps.
Pharmaceutical companies also have vast drug libraries that contain details of compounds and test results. Machine learning can rapidly assess information from these libraries to help researchers discover new insights and accelerate development.
Securing clinical trials
When a drug is ready to begin a clinical trial a critical medical supply chain begins. Technology is essential for drug companies, medical clinics and patients to ensure that clinical trials are conducted properly. Drugs must be received, stored and dispensed in a secure and efficient manner.
BoxLock’s rugged smart locks can be used to secure lockers and other storage units while providing real-time connectivity to a robust suite of access control, audit log and inventory management tools. The smart padlock devices use Wi-Fi or cellular networks to be deployed anywhere at scale.
To open a smart padlock device, a permissioned user scans a unique QR code identifier. The barcode scanning can facilitate real-time inventory tracking, date and time stamping, audit logs and chain of custody.
The subscription-based SaaS solution of BoxLock also has open APIs that can be used by drug companies and medical clinics to integrate access control and inventory data with their own systems to have real-time visibility and security controls within their existing software systems.
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