How do you calculate expected throughput for an automated chemistry platform and why is it important?

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Throughput is the rate at which a system can produce results, specifically the number of tests completed per hour. In an automated chemistry platform, this rate is determined by how long each assay run takes (assay runtime), how quickly samples can be loaded and fed into the system (sample loading cadence, including batching effects), and how often the instrument is unavailable for maintenance, calibration, or troubleshooting. Even a fast assay will yield a lower actual throughput if there are frequent downtimes or slow sample prep, because those delays reduce the total running time available in an hour. This makes throughput a practical measure for capacity planning and staffing: it tells you how many tests you can realistically deliver in a given period and thus how many operators, shifts, and resources you need to meet demand.

Other metrics address different questions: reagent cost per hour relates to expense, not production rate; the number of instruments suggests potential capacity but not the actual rate at which tests are completed; and average time to report results describes turnaround time per test, not the overall hourly production rate.