33rd
Accuracy Rank

Victor-Babaniyi

Victor Babaniyi
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-0.047933

Relative Brier Score
13836005101520253035
Questions Forecasted
1110-0.100.10.20.30.40.50.60.70.80.911.1
Scored Questions

50

Forecasts

9

Upvotes
Forecasting Activity
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Comments 0 0 53 53 53
Questions Forecasted 0 0 36 36 36
Upvotes on Comments By This User 0 0 9 9 9
 Definitions
New Badge
Victor-Babaniyi
earned a new badge:

Power Forecaster - Jan 2025

Earned for making 20+ forecasts in a month.
New Badge
Victor-Babaniyi
earned a new badge:

Star Commenter - Jan 2025

Earned for making 5+ comments in a month (rationales not included).
New Prediction
Why do you think you're right?

1. Regulatory Precedent:

a. No Class III neurotechnology (e.g., deep brain stimulation) has been approved for elective use in healthy individuals within 10 years of first human trials.

b. BCIs are fundamentally more invasive than most approved medical implants.

2. Safety & Ethical Barriers:

a. The FDA is conservative with elective medical procedures involving the central nervous system.

b. Long-term risks (e.g., brain tissue damage, unintended cognitive side effects) will require decades of study.

3. Lack of Market Pressure:

a. Unlike life-saving medical BCIs, elective neural implants lack an urgent need for approval.

Files
Why might you be wrong?

1. Regulatory Acceleration:

a. If Neuralink’s early trials prove extremely safe and effective, the FDA could fast-track approval.

b. The Breakthrough Device Program may allow for quicker approval if Neuralink positions its implant as a cognitive health aid (e.g., treating mild cognitive decline) rather than pure enhancement.

2. Military & National Security Interests:

a. DARPA and U.S. military are investing in invasive BCIs for combat pilots, intelligence analysts, and special forces.

b. If these devices show high effectiveness with minimal risk, they may enter the commercial market faster than expected.

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New Prediction
Why do you think you're right?

1. Current peptide synthesis methods may struggle with proteins this long.

2. Folding & stability issues could prevent functional verification.

3. Living cell-based synthesis remains more practical for complex proteins.



Files
Why might you be wrong?

1. AI-driven protein modeling (AlphaFold, Rosetta) is accelerating discoveries.

2. Flow chemistry & automated synthesis platforms are improving scalability.

3. Growing biotech funding ensures continued investment in synthetic proteins.

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New Prediction
Why do you think you're right?

1. Full whole-blood equivalents face massive safety and efficacy hurdles.

2. Regulatory risk remains high due to the FDA’s stringent blood product requirements.

3. Unexpected toxicity/clotting issues could halt clinical trials.

Files
Why might you be wrong?

1. Government/Military interest could lead to faster approvals (e.g., DARPA’s involvement).

2. Advances in synthetic RBCs are promising (e.g., ErythroMer).

3. Regulatory pathways for biologics have improved since previous failures.

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New Prediction
Victor-Babaniyi
made their 2nd forecast (view all):
Probability
Answer
30% (0%)
Chemical
5% (0%)
Biological
5% (-5%)
Radiological
10% (+5%)
Nuclear
Why do you think you're right?

1. Historical evidence supports chemical weapons usage even under international prohibitions.

2. Nuclear escalation risks have increased in volatile regions, particularly in conflicts where deterrence may fail.

3. States under extreme pressure (e.g., North Korea, Russia) may resort to desperate measures.

Files
Why might you be wrong?

1. Strong international deterrence mechanisms remain in place, and intelligence agencies have improved monitoring capabilities.

2. CBRN use has massive strategic consequences, making state actors hesitant unless facing existential threats.

3. State-sponsored non-state actors may use CBRN, but this forecast only considers direct state actions.

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New Prediction
Why do you think you're right?
1. Historical evidence supports chemical weapons usage even under international prohibitions.2. Nuclear escalation risks have increased in volatile regions, particularly in conflicts where deterrence may fail.3. States under extreme pressure (e.g., North Korea, Russia) may resort to desperate measures.
Files
Why might you be wrong?

1. Strong international deterrence mechanisms remain in place, and intelligence agencies have improved monitoring capabilities.

2. CBRN use has massive strategic consequences, making state actors hesitant unless facing existential threats.

3.State-sponsored non-state actors may use CBRN, but this forecast only considers direct state actions.

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New Prediction
Why do you think you're right?

None of the repurposed drugs for TBIs have succeeded in phase 3 trials, a significant hurdle.

TBIs involve highly variable pathologies across patients, making clinical efficacy harder to demonstrate.

By 2030, the time to complete preclinical work, clinical trials, and FDA approval may be insufficient.

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Why might you be wrong?

TBIs and neurodegenerative diseases share key mechanisms, making drugs targeting one potentially effective for the other.

AI and computational methods are accelerating drug repurposing, reducing the time to identify promising candidates.

The FDA has shown willingness to fast-track approvals for repurposed drugs in high-need areas.

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New Prediction
Victor-Babaniyi
made their 1st forecast (view all):
Probability
Answer
15%
Implantable Devices
35%
Environmental Sensors
40%
Personal Electronics
10%
Advanced Computing
Why do you think you're right?

The consumer wearables market is rapidly expanding, and bioelectronics fits seamlessly into this trend.

There is increasing global emphasis on sustainability and environmental monitoring.

Files
Why might you be wrong?

1. Unforeseen breakthroughs in Advanced Computing could shift the balance.

2. Stricter or looser-than-expected regulations could impact outcomes.

3. Changes in consumer priorities (e.g., privacy concerns with wearables) could hinder adoption.

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New Prediction
Why do you think you're right?

1. The FDA may remain cautious due to potential risks of bypassing in vivo studies.

2. In silico methods may not adequately model complex biological interactions.

3. Concerns over safety and efficacy might slow policy changes.


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Why might you be wrong?

Regulatory bodies have historically adapted to emerging technologies, though typically at a conservative pace.

2. Rapid advancements in AI and ML can make in silico models more credible and reliable.

3. Ongoing programs (e.g., Good Simulation Practices) show openness to change.


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