Using Real World Evidence to Build Dynamic Cohorts in Real-Time

Enabling formulations becomes more and more necessary to obtain adequate exposure of APIs during (pre)-clinical research. Currently, most registered formulations to improve bioavailability are based on lipidic systems, which make use of intrinsic digestion processes within the GI tract, facilitating the absorption of APIs. Aside from a general absorption mechanism, lipidic systems can also promote lymphatic transport of poorly soluble drugs, such as hormones. In addition, many different indications, such as HIV therapy, oncology, immunosuppressant and even arising therapies related to medicinal cannabis (e.g. CBD) can benefit from lipid formulations. These formulations create multiple possibilities for oral administration because they can be manufactured as solutions, suspensions, emulsions, and self-(micro)emulsifying systems.

Typically, Manufacturing Operations and Support Personnel spend too much time trying to navigate a complex information landscape to locate data, extract it and combine it with data from other systems to gain insights about the assets and drug manufacturing processes they support and service. At Eli Lilly, as a part of their Digital Plant journey, a program called “DaVinci” (among many others) was created to address this problem head-on. DaVinci is a comprehensive data integration platform with embedded data visualization, analytics, and knowledge sharing capability that also provides the flexibility for users to bring their own data and tools to the platform via “plug and play” functionality. It also provides a shared workbench to conduct quick analytics on near-real-time data to gain timely insights on manufacturing processes.

Speed, Quality & Cost – Why You Should be Conducting Your Clinical Trials. Join PCI Clinical Services and their partners for this educational webinar to learn tax incentive program and eligibility when conducting your trials in Australia

Sequence variants (SVs) are protein isoforms that contain one or more unintended amino acid substitutions. They can arise at a single amino acid site due to a genetic (RNA/DNA) mutation or at multiple amino acid locations, potentially due to translational errors, also referred to as misincorporations. The ability to detect SVs in protein biotherapeutics is critical due to their potential impact on structural/functional characteristics, safety, and efficacy. Trypsin peptide mapping with liquid chromatography-ultrahigh resolution tandem mass spectrometry (LC-MS/MS) provides the ideal workflow for the detection, identification, and relative quantitation of both genetic and translational SVs.