As of 29 November 2025, the 10‑year window Friedberg named ("over the next ten years" from 2021, i.e., roughly through 2031) is only about halfway over, and the key parts of his prediction are only partially testable.

What has clearly happened (supports parts of the claim):

1. The area is being “chased really hard” this decade.

   • Major pharma companies have launched explicit quantum‑chemistry and drug‑discovery collaborations (e.g., Boehringer Ingelheim with Google Quantum AI for molecular dynamics and drug design; Roche with Cambridge Quantum; Merck with SEEQC). (en.wikipedia.org)
   • Cloud and platform providers have built chemistry/life‑science offerings around NISQ hardware, such as Microsoft’s Azure Quantum Elements, explicitly targeted at materials, chemistry, and pharmaceutical R&D. (en.wikipedia.org)
   • Investment vehicles like Novo Holdings have committed hundreds of millions of dollars to quantum‑computing startups with a stated focus on life sciences, including protein modeling and accelerating drug discovery. (reuters.com)
   • Numerous reviews and road‑mapping pieces in 2023–2025 outline quantum computing as a key near‑term application for generative chemistry and drug discovery, specifically emphasizing the use of noisy intermediate‑scale quantum (NISQ) devices. (pubmed.ncbi.nlm.nih.gov)
     Conclusion: The claim that this application area would be actively and broadly pursued during the 2020s is already correct.

2. Noisy / pre‑fault‑tolerant devices are being used for real molecular and materials simulations, including some non‑toy results.

   • IBM’s work on "quantum utility" shows noisy quantum processors (e.g., Heron) solving Ising‑model problems relevant to materials science beyond brute‑force classical simulation, marking a first practical regime where NISQ devices provide scientifically useful results. (newswire.ca)
   • Hybrid quantum–classical algorithms like Quantum‑Selected Configuration Interaction (QSCI) have been used by IBM and partners to push chemical computations "beyond the scale of exact diagonalization" on classical machines, demonstrating the largest‑scale chemistry simulations on quantum hardware to date. (en.wikipedia.org)
   • Google’s 2025 Quantum Echoes algorithm, running on the noisy 105‑qubit Willow processor, achieved a quantum advantage benchmark about 13,000× faster than the best classical methods and was applied to NMR‑related molecular dynamics, uncovering previously unknown atomic structures in molecules with 15 and 28 atoms. (reuters.com)
   • A 2024 Nature paper (summarized in Drug Discovery News) and related work show hybrid quantum computing applied to realistic drug‑discovery tasks (e.g., prodrug activation energetics and covalent KRAS‑G12C inhibition by sotorasib), demonstrating that small noisy quantum devices can contribute to modeling non‑toy chemical problems. (drugdiscoverynews.com)
     Conclusion: We do see genuine research breakthroughs in quantum simulations of molecules and materials on noisy hardware, consistent with his claim that “super noisy, super low fidelity” machines would start yielding breakthroughs this decade.

What has not clearly happened yet (limits of the claim as of 2025):

1. No widely accepted, end‑to‑end “practical breakthrough” in enzyme/drug design attributable to NISQ quantum computers.
   Recent surveys and industry analyses still describe quantum computing for drug discovery as early‑stage / emerging, with tools “limited in availability” as of mid‑2025 and use cases framed as proofs of concept or pilots rather than standard industrial workhorses. (mdpi.com)
   Reviews on quantum computing in drug discovery and medicine emphasize potential and early demonstrations, but do not report approved drugs, industrial enzymes, or nitrogen‑fixation catalysts that owe their discovery primarily to quantum computers. (mdpi.com)
   In other words, most impact so far is in research demos and methodology, not yet in widely acknowledged breakthroughs like new commercial enzymes or drugs designed thanks to quantum advantage.

2. His strong sub‑claim that “we already have enough compute power” remains questionable.
   Even in 2020–2022, experts in quantum‑accelerated drug discovery repeatedly noted that hardware was “still in its infancy” and "not quite at a scale" to solve the toughest real‑world drug problems, and more recent work still frames many life‑science applications as contingent on further scaling and error‑correction over the next decade. (pharmaceutical-technology.com)
   The most advanced 2024–2025 results (e.g., Willow + Quantum Echoes, hybrid pipelines) are still presented as stepping stones toward practical drug and materials design, not evidence that today’s NISQ machines are already sufficient for the full class of industrially relevant problems Friedberg invoked. (livescience.com)

Why the overall verdict is “inconclusive” rather than right or wrong:

• The strongest, most specific part of Friedberg’s prediction is that within about 2021–2031, noisy quantum computers will deliver practical breakthroughs in simulating quantum states of materials/atoms/molecules that directly translate into things like better enzymes for nitrogen fixation, drug discovery, or targeted proteins, using the compute power already available at the time he spoke.
• By late 2025, we do have:
  • Widespread pursuit of exactly these applications in industry and academia. (en.wikipedia.org)
  • Credible, noisy‑hardware demonstrations of non‑toy molecular simulations and even quantum advantage on chemistry‑related benchmarks. (newswire.ca)
• But we do not yet have clear, broadly agreed‑upon industrial outcomes like new approved drugs or widely deployed enzymes that owe their discovery to these NISQ simulations; authoritative sources still characterize this as a developing, not yet fully realized, capability. (mdpi.com)
• Since his horizon runs until roughly 2031, there is still substantial time for such practical breakthroughs to emerge as hardware and algorithms continue to improve.

Because an essential part of his prediction concerns outcomes by the end of the decade and those outcomes have neither clearly materialized nor clearly failed by 2025, the fairest assessment today is “inconclusive (too early)” rather than definitively right or wrong.