This article will explain what Big Data and small data are, build your fluency with the benefits and risks of each, and provide recommendations to improve our data-rich future.
Recently, a pharmaceutical executive raised an interesting question in the media. To paraphrase, he asked, “What should a corporate entity do when it has new information that is material to its financial situation and that new information is ‘under embargo’ until it is either published in a journal or presented at a scientific meeting?”
Integrated delivery networks (IDNs) were among the earliest adopters of Medicare accountable care organization (ACO) programs. The Centers for Medicare and Medicaid Services (CMS) releases results specific to these programs on an annual basis, creating opportunities for new drug development.
New York City has long aspired to become a life sciences hub, but while the city seems to have all the elements necessary to foster such industry growth, it has continually fallen short of this goal. New York currently ranks a distant third behind both Greater Boston and the San Francisco Bay Area, and there’s some work to do if it hopes to catch up.
Fall conference season is upon us and a cursory internet search shows no less than a half-dozen conferences focused on the topic of patient-centricity. Thankfully, the momentum around the topic continues as sponsors and CROs strive to find more patient-centric approaches to conducting clinical trials.
Real-world evidence is a hot topic in clinical research right now. But too often, the massive amounts of data now available from electronic medical records used in routine medical practice are being considered to be clinical evidence to support medical decision making. However, the process of transforming these large data sources into actionable evidence that can change clinical practice is a complicated but important endeavor.
Artificial intelligence (AI) has truly moved from concept to reality in the pharmaceutical industry. Many companies are already using AI to pour through mountains of scientific data in an effort to speed and improve the drug discovery process. And the technology is starting to find new applications in areas as diverse as regulatory/compliance, clinical trials, manufacturing, and supply chain.
The genome editing market is estimated to reach $3.5 billion in 2019 — an increase from $2 billion in 2014 — with a CAGR of 13 to 14 percent. The factors driving this market include increased R&D funding for genomic research, a growing demand for synthetic genes, new technologies in genome editing, and high utilization in plant breeding. However, high regulatory stringencies, lengthy approval processes, and ethical issues associated with the fear of genetic research hamper market growth. This article examines the utilization of genome editing tools and technology and their impact across the drug discovery industry.
With the age of remote clinical trials upon us, it bears asking: What do these trials mean for the common business-related tasks of clinical trials? One under-emphasized place of change will likely be investigator site budgets.