Policy Impact Analysis - 117/S/3553

Bill Overview

Title: Agility in Manufacturing Preparedness Act

Description: This bill requires the Department of Health and Human Services (HHS) to seek to contract with the National Institute for Innovation in Manufacturing Biopharmaceuticals to assess and make recommendations concerning U.S. capabilities for biopharmaceutical manufacturing and related matters. HHS must coordinate with the Biomedical Advanced Research and Development Authority on this contract.

Sponsors: Sen. Rubio, Marco [R-FL]

Target Audience

Population: Individuals employed in biopharmaceutical manufacturing and related sectors

Estimated Size: 250000

Reasoning

Simulated Interviews

Biopharmaceutical Manufacturer (Boston, MA)

Age: 45 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 4/20

Statement of Opinion:

  • The policy might enhance our competitive edge in global markets.
  • I expect investments to follow in the future leading to job stability.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 6
Year 3 7 6
Year 5 8 6
Year 10 8 5
Year 20 8 5

Biotechnology Researcher (San Diego, CA)

Age: 30 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 5/20

Statement of Opinion:

  • It could steer more funding towards R&D that we can benefit from.
  • Initial changes might not be visible but future growth potential is exciting.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 6 6
Year 3 7 6
Year 5 7 6
Year 10 8 6
Year 20 8 6

Logistics Coordinator (Raleigh, NC)

Age: 50 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 7.0 years

Commonness: 7/20

Statement of Opinion:

  • Potential for increased logistic demands and technology upgrades.
  • I am cautiously optimistic about the strategic benefits.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 5
Year 2 5 5
Year 3 6 5
Year 5 6 5
Year 10 6 5
Year 20 6 5

Software Engineer (Austin, TX)

Age: 38 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 4.0 years

Commonness: 6/20

Statement of Opinion:

  • Not sure about immediate changes to my role but could lead to more projects.
  • Long-term investments in infrastructure can improve work satisfaction.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 9 8
Year 5 9 8
Year 10 9 8
Year 20 9 8

Healthcare Policy Analyst (Miami, FL)

Age: 29 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 0.0 years

Commonness: 8/20

Statement of Opinion:

  • This policy might not change the immediate landscape but could inform future regulations.
  • A step forward in considering our infrastructure capabilities.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 7 7
Year 20 7 7

Factory Worker (Detroit, MI)

Age: 55 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 10/20

Statement of Opinion:

  • I doubt it'll change things much here unless projects expand.
  • Hoping for more resources or projects but not counting on it soon.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 6 6
Year 3 6 6
Year 5 7 6
Year 10 7 6
Year 20 7 6

Supply Chain Analyst (Newark, NJ)

Age: 42 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 8.0 years

Commonness: 5/20

Statement of Opinion:

  • Strategic plans like this could spur investments in supply chain tech.
  • Encouraged by a framework that acknowledges the need for manufacturing capabilities.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 6
Year 3 8 6
Year 5 8 6
Year 10 9 6
Year 20 9 6

Biotech Startup Founder (Seattle, WA)

Age: 27 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 5.0 years

Commonness: 3/20

Statement of Opinion:

  • Optimistic for potential grant redirections or consideration of innovative startups.
  • This is mostly a starting point but aligns with growth strategies for startups.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 9 8
Year 5 9 8
Year 10 9 8
Year 20 9 8

Retired (Philadelphia, PA)

Age: 60 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 0.0 years

Commonness: 4/20

Statement of Opinion:

  • Hopeful that this policy signals a commitment to expanding bioscientific capabilities.
  • Feels positive about mentoring opportunities for the younger workforce.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 7 7
Year 20 7 7

Regulatory Affairs Specialist (Chicago, IL)

Age: 36 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 6.0 years

Commonness: 7/20

Statement of Opinion:

  • Legislative policies like this one are crucial indicators of where we are headed.
  • Expect limited immediate impact on day-to-day work until more data is available.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 6 6
Year 3 6 6
Year 5 7 6
Year 10 7 6
Year 20 7 6

Cost Estimates

Year 1: $5000000 (Low: $4000000, High: $6000000)

Year 2: $5000000 (Low: $4000000, High: $6000000)

Year 3: $5000000 (Low: $4000000, High: $6000000)

Year 5: $5000000 (Low: $4000000, High: $6000000)

Year 10: $0 (Low: $0, High: $0)

Year 100: $0 (Low: $0, High: $0)

Key Considerations