Weighted Drug Audit Sampling via Distributed Ledger
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Solution Overview
Problem
Conventional random sampling methods for auditing pharmaceutical products are inflexible and burdensome, particularly for smaller entities in the pharmaceutical supply chain, as they do not account for population size or supply chain realities, leading to biased and unfair sampling.
Innovation Solution
A computer-implemented method using distributed ledger technology to select a subset of drug product records based on weighted probabilities, which are adjusted according to specific criteria such as location population size and supply chain levels, ensuring a fair and flexible sampling process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pure random sampling is used for audit selection, then every pharmaceutical product has an equal chance of being selected, but smaller entities and states with smaller populations bear an undue burden compared to their market share
Solution Approach 1:
The patent changes the sampling parameter from uniform random selection to weighted random selection, where weights are inversely proportional to population size or market share. This ensures that smaller entities have a higher probability of selection relative to their size, maintaining fairness while reducing disproportionate burden. The weighted probability formula P(i) = w(i) / Σw(j) where w(i) represents the weight of entity i implements this parameter change.
Solution Approach 2:
The patent applies different selection probabilities to different entities based on their local characteristics (population size, market share). Instead of a one-size-fits-all approach, each entity receives a customized selection probability tailored to its specific context, ensuring that the audit burden is appropriately distributed according to local realities.
2Ease of manufacture
If conventional random sampling is used, then the selection process is simple to implement, but it lacks flexibility to account for supply chain realities and population size variations
Solution Approach 1:
The patent introduces dynamic weighting factors that can be adjusted based on supply chain realities, population size, and other relevant criteria. The system transitions from a static uniform sampling approach to a dynamic weighted sampling approach where probabilities can be modified to reflect changing conditions and specific audit requirements, enhancing adaptability while maintaining computational efficiency.
3Measurement precision
If weighted probability sampling is implemented to account for population size and supply chain levels, then the sample becomes more representative and fair, but the selection process becomes more complex
Solution Approach 1:
The patent replaces manual judgment-based sample selection with an automated computational system that calculates weighted probabilities and performs random selection according to the weighted distribution. This substitution of mechanical/computational processes for manual processes reduces the practical complexity burden on auditors while achieving more precise and representative sampling.
Data Source
AI summary
A computer-implemented method of auditing drug supply chain data gathered from a distributed ledger is disclosed. The method includes receiving a population of drug product records from the distributed ledger. The method includes receiving a first set of drug product criteria. The method includes determining a weighted probability for one or more drug product records of the population of drug product records. The method includes generating a randomized first subset of drug product records from the population of drug product records based on the weighted probability of the one or more drug product records. Other methods, systems, and the like for unbiased drug selection for audit are also disclosed.