Has the COVID-19 Crisis Affected the Growth of United States Food and Drug Administration Drug Approvals? The Answer is Not Yet! A Time Series (Forecasting) Study
Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-19; HCoV-19; COVID-19) has affected all daily activities. Has it also affected the number of United States (FDA) drug approvals over time? The short answer from empirical time series forecasting is not yet. Care should be taken as the crisis continues through maintaining the scientific, economic, political, and social supportive structures to sustain momentum. This conclusion is based on analyzing the results of (non-overlapping) forecasting routines (viz., complex exponential smoothing, auto-regressive fractionally integrated moving average, extreme learning machine, and multi-layer perceptron) performed on longitudinal (1939-present) FDA (CDER) drug approvals taking into regard pre- and extant-COVID-19 eras. This is an initial study and there are caveats with the approach, and as such, all data and programs are provided to support replication of the results and furthering of the investigation..
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:55 |
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| Enthalten in: |
Therapeutic innovation & regulatory science - 55(2020), 3 vom: 26. Dez., Seite 553-557 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Daizadeh, Iraj [VerfasserIn] |
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| Links: |
Volltext [lizenzpflichtig] |
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| Themen: |
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| Anmerkungen: |
© The Drug Information Association, Inc 2020 |
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| doi: |
10.1007/s43441-020-00249-6 |
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| funding: |
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| 520 | |a Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-19; HCoV-19; COVID-19) has affected all daily activities. Has it also affected the number of United States (FDA) drug approvals over time? The short answer from empirical time series forecasting is not yet. Care should be taken as the crisis continues through maintaining the scientific, economic, political, and social supportive structures to sustain momentum. This conclusion is based on analyzing the results of (non-overlapping) forecasting routines (viz., complex exponential smoothing, auto-regressive fractionally integrated moving average, extreme learning machine, and multi-layer perceptron) performed on longitudinal (1939-present) FDA (CDER) drug approvals taking into regard pre- and extant-COVID-19 eras. This is an initial study and there are caveats with the approach, and as such, all data and programs are provided to support replication of the results and furthering of the investigation. | ||
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