Rationale

• Serious and life-threatening adverse drug events (ADEs) may not be detected or adequately quantified in small scale clinical trials and may only be illuminated after thousands or millions of patients are treated with a new medication. This is especially true for high-risk, vulnerable patients with the greatest therapeutic need, but who are often excluded from new medication trials. Thus, medication safety must be assessed following regulatory approval; however, the current paradigm of post-approval pharmacovigilance is notably deficient.

Innovation

• COHRDATA’s Pharmacovigilance & Drug Safety Initiative employs systematic strategies to proactively detect “known” and “unknown” medication-related safety signals and confirm the causal association between medication exposure and adverse drug events (ADEs). By employing the following enhancements, the Pharmacovigilance & Drug Safety Initiative transcends the limitations of the current paradigm:

• Real World Data Integration: Transitioning from the inherent biases of voluntary or “spontaneous” adverse drug event (ADE) reporting systems, the Pharmacovigilance & Drug Safety Initiative’s integration of comprehensive real world data (RWD) captures critical details pertaining to medication exposure, reveals unreported ADEs, and includes detailed patient narratives. This novel utilization of RWD signifies a sea change in safeguarding public health.

• Surveillance Amplified: A departure from passive safety signal surveillance, The Pharmacovigilance & Drug Safety Initiative actively detects medication-linked safety signals exposing otherwise concealed patient harm using systematic and innovative methods.

• Contextual Understanding: Elevating from isolated safety signals devoid of context, the Pharmacovigilance & Drug Safety Initiative employs rigorous methodology to identify, contextualize, and confirm adverse drug events thereby generating robust inferences regarding medication related harm.

Benefactors

• The Pharmacovigilance & Drug Safety Initiative empowers patients, healthcare providers, drug manufacturers and regulators with critical information aimed to:

  • Reveal true ADE risk

  • Improve the accuracy of drug labeling with respect to ADE risk 

  • Mitigate future ADE risk through safer medication prescribing practices

Objectives

• Aim 1. To describe the prevalence of target medication exposure.

• Aim 2. To identify and describe known and unknown - “suspected” adverse drug events (S-ADEs) - associated with target medications.

• Aim 3. To estimate the crude association of S-ADEs with target medication exposure.

  • When a significant crude association is observed, the S-ADE will be reclassified as a “probable” adverse drug event (P-ADE)

• Aim 4. To estimate the causal association of P-ADEs with target medication exposure.

  • When a significant causal association is observed, the P-ADE will be reclassified as a “confirmed” adverse drug events (C-ADE)