Evidence map›Paper›PMID 42427764›Full record

ArticlebioRxiv : the preprint server for biology2026

Practical Use of Advanced AI Frameworks on Real-Life Scientific Problems: Three Case Studies.

Halime S A Gulluoglu, Jibin Baby, Kirti M Bagul, Bhuvan R Basangari, S Akash Bathini, Nikhil K R Chalamalla, Jude Dcunha, Om Gupta, Lanqin Huang, Xutong Jiang and 11 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Halime S A GulluogluCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Jibin BabyCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Kirti M BagulCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Bhuvan R BasangariCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
S Akash BathiniCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Nikhil K R ChalamallaCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Jude DcunhaCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Om GuptaCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Lanqin HuangCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Xutong JiangCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Yashas R NaiduCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Gokul SathishkumarCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Mayank SehrawatCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
S Lakshmi ThotaCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Dheeraj ThuvaraCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Mahesh B VanguriCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Jiaxi YinCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.
Bat-Erdene JugderBioscience Immunology, Research and Early Development, Respiratory and Immunology, Biopharmaceuticals R&D, AstraZeneca, Waltham, MA 02451, USA.
Isabel E LuskyBorch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA.
Jianing LiBorch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA.
Anton V SinitskiyCollege of Professional Studies, Northeastern University, Boston, MA 02115, USA.ORCID 0000-0002-8610-0162

Funding

Precision Design of Antimicrobial Peptides Against Bacterial InfectionsR01GM143370 · NIGMS · PURDUE UNIVERSITY · PI LI, JIANING · 2022 to 2025
$1.2M
NIGMS NIH HHS R01 GM143370
6 · The paper itself

Abstract

Agentic artificial intelligence (AI) systems increasingly claim to automate scientific research, yet independent evaluations report persistent gaps between those claims and demonstrated capability. We tested frontier agentic AI systems on three practical problems: prediction of treatment non-response in immune-mediated inflammatory diseases, optical chemical structure recognition for literature mining, and prediction of drug-design-related properties from small datasets. Each problem was first assigned to autonomous frameworks and then reattempted as human-led, AI-assisted work. Autonomous runs failed in most cases, while human-led work produced reusable resources and modest but defensible performance, including new evidence for possible mechanisms of treatment resistance and a more practical benchmark for mining chemical structures from scientific papers. Property prediction was the single task on which one autonomous AI framework matched the human expert. We conclude that current frameworks can carry out engineering and analysis once a human expert leads the project, but cannot yet engineer a novel solution without oversight. The use of AI on real-life scientific problems remains an art rather than a routine technology.

Identifiers

PMID42427764
PMCPMC13345091

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.