Adverse Event Detection

Adverse Drug Reaction Detection

Disproportionality Analysis

class AdverseEventDetector:
    def __init__(self, case_reports, population):
        self.cases = case_reports
        self.pop = population

    def compute_prr(self, drug, event):
        a = self.cases[(self.cases['drug'] == drug) & (self.cases['event'] == event)].shape[0]
        b = self.cases[self.cases['drug'] == drug].shape[0] - a
        c = self.cases[self.cases['event'] == event].shape[0] - a
        d = self.cases.shape[0] - a - b - c
        if b == 0 or c == 0: return 1
        return (a / (a + b)) / (c / (c + d))

Signal Detection from EHR

ML-Based Detection

class EHRSignalDetector:
    def detect_signals(self, medication_events):
        signals = {}
        for drug in medication_events['drug'].unique():
            for event in medication_events['event'].unique():
                prr = self.compute_prr(drug, event)
                if prr >= 2:
                    signals[(drug, event)] = {'prr': prr, 'confidence': self._bootstrap_ci(drug, event)}
        return signals

Pharmacovigilance ML

Causality Assessment