Category: 3. Business

  • Diamyd Medical accelerates primary efficacy readout by 9 months in type 1 diabetes Phase 3 trial following FDA alignment and guidance

    STOCKHOLM, Dec. 29, 2025 /PRNewswire/ — Diamyd Medical has reached alignment with the U.S. Food and Drug Administration (FDA) to accelerate the primary efficacy readout in its ongoing pivotal, registrational Phase 3 DIAGNODE-3 trial in type 1 diabetes from 24 to 15 months, per FDA guidance, enabling the full primary efficacy readout of the trial to occur nine months earlier than previously planned and communicated. The previously announced interim efficacy readout, involving approximately 170 participants with 15-month data, remains on track for the end of March 2026 and may support an accelerated BLA pathway, consistent with FDA guidance.

    “We are very pleased with the FDA’s feedback as it provides a clear way forward,” says Ulf Hannelius, CEO of Diamyd Medical. “The proposed change meaningfully shortens the timeline to the full primary efficacy readout in our registrational Phase 3 trial, while maintaining a robust assessment of long-term efficacy. We remain focused on the upcoming interim efficacy readout in March 2026, which is on track as the next key catalyst in our efforts to bring this therapy to patients with type 1 diabetes.”

    The trial’s co-primary efficacy endpoints, C-peptide area under the curve (AUC), a marker of endogenous insulin production, and HbA1c, a measure of blood sugar control, were originally defined at 24 months. Following a recent Type C meeting, and consistent with FDA guidance, the FDA agreed with the Company’s proposal to change the timepoint for the primary efficacy readout to 15 months, with a formal protocol amendment to be submitted for FDA review. The originally planned 24-month assessment will be retained as a secondary endpoint to assess durability of the treatment effect of Diamyd®.

    DIAGNODE-3 is a randomized, double-blind, placebo-controlled Phase 3 trial evaluating Diamyd® in approximately 300 genetically defined individuals with Stage 3 type 1 diabetes. Diamyd® is a precision-medicine, antigen-specific immunotherapy designed to preserve endogenous insulin production.

    The FDA has granted Fast Track Designation for Diamyd® across Stages 1-3 of type 1 diabetes, Orphan Drug Designation for Stage 3 type 1 diabetes, and has confirmed C-peptide as an acceptable surrogate endpoint that may support an accelerated approval pathway in the United States.

    About Diamyd Medical

    Diamyd Medical develops precision medicine therapies to prevent and treat type 1 diabetes. Diamyd® is an investigational antigen-specific immunomodulatory therapeutic for the preservation of endogenous insulin production specifically for individuals carrying an HLA DR3-DQ2 gene. Diamyd® has been granted Orphan Drug Designation in the U.S. as well as Fast Track Designation by the U.S. FDA for the treatment of Stage 3 (clinically diagnosed symptomatic) type 1 diabetes. Diamyd® has also been granted Fast Track Designation for the treatment of Stage 1 and 2 (pre-symptomatic) type 1 diabetes. DIAGNODE-3, a confirmatory Phase 3 trial with potential for an accelerated approval pathway in the US is actively recruiting patients with recent-onset (Stage 3) type 1 diabetes at 57 clinics in eight European countries and in the US. Significant results in preserving endogenous insulin production have previously been shown in a large genetically predefined patient group – both in a large-scale meta-analysis as well as in the Company’s prospective European Phase 2b trial. The DIAGNODE-3 trial is recruiting only this patient group that carries the common genotype known as HLA DR3-DQ2, which constitutes approximately 40 % of patients with type 1 diabetes in Europe and the US. A biomanufacturing facility is under development in Umeå, Sweden, for the manufacture of recombinant GAD65 protein, the active ingredient in the antigen-specific immunotherapy Diamyd®. Diamyd Medical is a major shareholder in the stem cell company NextCell Pharma AB and in the artificial intelligence company MainlyAI AB.

    Diamyd Medical’s B share is traded on Nasdaq First North Growth Market under the ticker DMYD B. FNCA Sweden AB is the Company’s Certified Adviser.

    For further information, please contact:
    Ulf Hannelius, President and CEO
    Phone: +46 736 35 42 41
    E-mail: [email protected]

    Diamyd Medical AB (publ)
    Box 7349, SE-103 90 Stockholm, Sweden. Phone: +46 8 661 00 26, Fax: +46 8 661 63 68
    E-mail: [email protected] Reg. no.: 556242-3797 Website: https://www.diamyd.com

    This information was brought to you by Cision http://news.cision.com.

    https://news.cision.com/diamyd-medical-ab/r/diamyd-medical-accelerates-primary-efficacy-readout-by-9-months-in-type-1-diabetes-phase-3-trial-fol,c4287010

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  • Diamyd Medical accelerates primary efficacy readout by 9 months in type 1 diabetes Phase 3 trial following FDA alignment and guidance

    STOCKHOLM, Dec. 29, 2025 /PRNewswire/ — Diamyd Medical has reached alignment with the U.S. Food and Drug Administration (FDA) to accelerate the primary efficacy readout in its ongoing pivotal, registrational Phase 3 DIAGNODE-3 trial in type 1 diabetes from 24 to 15 months, per FDA guidance, enabling the full primary efficacy readout of the trial to occur nine months earlier than previously planned and communicated. The previously announced interim efficacy readout, involving approximately 170 participants with 15-month data, remains on track for the end of March 2026 and may support an accelerated BLA pathway, consistent with FDA guidance.

    “We are very pleased with the FDA’s feedback as it provides a clear way forward,” says Ulf Hannelius, CEO of Diamyd Medical. “The proposed change meaningfully shortens the timeline to the full primary efficacy readout in our registrational Phase 3 trial, while maintaining a robust assessment of long-term efficacy. We remain focused on the upcoming interim efficacy readout in March 2026, which is on track as the next key catalyst in our efforts to bring this therapy to patients with type 1 diabetes.”

    The trial’s co-primary efficacy endpoints, C-peptide area under the curve (AUC), a marker of endogenous insulin production, and HbA1c, a measure of blood sugar control, were originally defined at 24 months. Following a recent Type C meeting, and consistent with FDA guidance, the FDA agreed with the Company’s proposal to change the timepoint for the primary efficacy readout to 15 months, with a formal protocol amendment to be submitted for FDA review. The originally planned 24-month assessment will be retained as a secondary endpoint to assess durability of the treatment effect of Diamyd®.

    DIAGNODE-3 is a randomized, double-blind, placebo-controlled Phase 3 trial evaluating Diamyd® in approximately 300 genetically defined individuals with Stage 3 type 1 diabetes. Diamyd® is a precision-medicine, antigen-specific immunotherapy designed to preserve endogenous insulin production.

    The FDA has granted Fast Track Designation for Diamyd® across Stages 1-3 of type 1 diabetes, Orphan Drug Designation for Stage 3 type 1 diabetes, and has confirmed C-peptide as an acceptable surrogate endpoint that may support an accelerated approval pathway in the United States.

    About Diamyd Medical

    Diamyd Medical develops precision medicine therapies to prevent and treat type 1 diabetes. Diamyd® is an investigational antigen-specific immunomodulatory therapeutic for the preservation of endogenous insulin production specifically for individuals carrying an HLA DR3-DQ2 gene. Diamyd® has been granted Orphan Drug Designation in the U.S. as well as Fast Track Designation by the U.S. FDA for the treatment of Stage 3 (clinically diagnosed symptomatic) type 1 diabetes. Diamyd® has also been granted Fast Track Designation for the treatment of Stage 1 and 2 (pre-symptomatic) type 1 diabetes. DIAGNODE-3, a confirmatory Phase 3 trial with potential for an accelerated approval pathway in the US is actively recruiting patients with recent-onset (Stage 3) type 1 diabetes at 57 clinics in eight European countries and in the US. Significant results in preserving endogenous insulin production have previously been shown in a large genetically predefined patient group – both in a large-scale meta-analysis as well as in the Company’s prospective European Phase 2b trial. The DIAGNODE-3 trial is recruiting only this patient group that carries the common genotype known as HLA DR3-DQ2, which constitutes approximately 40 % of patients with type 1 diabetes in Europe and the US. A biomanufacturing facility is under development in Umeå, Sweden, for the manufacture of recombinant GAD65 protein, the active ingredient in the antigen-specific immunotherapy Diamyd®. Diamyd Medical is a major shareholder in the stem cell company NextCell Pharma AB and in the artificial intelligence company MainlyAI AB.

    Diamyd Medical’s B share is traded on Nasdaq First North Growth Market under the ticker DMYD B. FNCA Sweden AB is the Company’s Certified Adviser.

    For further information, please contact:
    Ulf Hannelius, President and CEO
    Phone: +46 736 35 42 41
    E-mail: [email protected]

    Diamyd Medical AB (publ)
    Box 7349, SE-103 90 Stockholm, Sweden. Phone: +46 8 661 00 26, Fax: +46 8 661 63 68
    E-mail: [email protected] Reg. no.: 556242-3797 Website: https://www.diamyd.com

    This information was brought to you by Cision http://news.cision.com.

    https://news.cision.com/diamyd-medical-ab/r/diamyd-medical-accelerates-primary-efficacy-readout-by-9-months-in-type-1-diabetes-phase-3-trial-fol,c4287010

    The following files are available for download:

    SOURCE Diamyd Medical AB

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  • EBRD supports green lending in Uzbekistan

    EBRD supports green lending in Uzbekistan

    • EBRD to lend up to US$30 million to Hamkorbank
    • Funds to support green lending in Uzbekistan
    • Concessional co-financing to be provided by the HIPCA

    The European Bank for Reconstruction and Development (EBRD) is helping micro, small and medium-sized enterprises (MSMEs) in Uzbekistan to improve their access to green finance and promote green innovation by providing fresh funds under its Uzbekistan Green Economy Financing Facility II (GEFF II Uzbekistan).

    An EBRD loan of up to US$30 million (€25.7 million) under GEFF II Uzbekistan will allow Hamkorbank to expand its energy-efficiency lending to companies and households across the country, who can use the funds to modernise production, increase their energy efficiency and improve their climate resilience. The loan will be supported by concessional co-financing provided by the government of Canada under the High-Impact Partnership on Climate Action (HIPCA).

    HIPCA donors include: Austria, Canada, Finland, Germany, the Netherlands, Norway, South Korea, Spain, Switzerland, the TaiwanICDF (International Cooperation and Development Fund), the United Kingdom and the United States of America.

    The EBRD has invested over US$6.6 billion in Uzbekistan to date through 196 projects, with the majority of those funds supporting private entrepreneurship, contributing to the country’s economic development.

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  • PSX achieves another milestone, surpasses 174,000 points – RADIO PAKISTAN

    1. PSX achieves another milestone, surpasses 174,000 points  RADIO PAKISTAN
    2. KSE-100 hits new all-time high on nearly 1,500-point rally  Business Recorder
    3. PSX hits new peak on UAE investment hopes  Dawn
    4. Stock market gains 1,495 points to close at 173,896  The Nation (Pakistan )
    5. KSE-100 jumps past 174,000 as stocks open final week on strong note  Profit by Pakistan

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  • Stocks Hover Near Record, Silver Turns Volatile: Markets Wrap

    Stocks Hover Near Record, Silver Turns Volatile: Markets Wrap

    (Bloomberg) — Global stocks held gains from a record-breaking run fueled by artificial intelligence that’s helped markets rebound from an April slump sparked by tariff concerns. Volatility gripped precious metals such as silver, which climbed to another all-time high.

    The MSCI All Country World Index — one of the broadest measures of the equity market — was steady after rising 1.4% last week to a new high as a much-expected year-end rally took hold. A gauge of Asian shares advanced 0.3% in a seventh straight day of gains, boosted by tech and industrials. European futures rose 0.3% while contracts on the S&P 500 edged lower after the US benchmark finished near its peak on Friday.

    Silver gyrated after smashing through $80 an ounce for the first time amid a historic surge powered by speculative trades and a persistent mismatch between supply and demand. Gold was down more than 1% after reaching a fresh high in the previous session, while copper jumped more than 6% to hit a record on the London Metal Exchange.

    Precious metals have emerged as a hot corner of financial markets in recent months, boosted by elevated central-bank purchases, inflows to exchange-traded funds and three successive rate cuts by the Federal Reserve. Lower borrowing costs are a tailwind for the commodities, which don’t pay interest, and traders are betting on more rate cuts in 2026.

    “We are witnessing a generational bubble playing out in silver,” Tony Sycamore, market analyst at IG Australia, wrote in a note Sunday. “Relentless industrial demand from solar panels, EVs, AI data centers and electronics, pushing against depleting inventories, has driven physical premiums to extremes.”

    Monday’s early momentum for precious metals had come after a comment by Elon Musk over the weekend that highlighted the growing investor frenzy around them. Musk replied to a tweet on Chinese export restrictions by saying on X: “This is not good. Silver is needed in many industrial processes.”

    In the last week, frictions in Venezuela — where the US has blockaded oil tankers — and strikes by Washington on Islamic State in Nigeria have also added to the haven appeal of these metals. With silver inventories near their lowest on record, there’s a risk of supply shortages that could impact multiple sectors.

    What Bloomberg strategists say…

    “Silver has particular drivers which mean it is understandable for it to be outperforming the general rally in metals, precious and otherwise, against the US dollar. Nevertheless it is very tough to justify the parabolic ramp-up in silver as it leaves peers behind.”

    Garfield Reynolds, Markets Live Strategist. For full analysis, click here.

    In geopolitical news, President Donald Trump said he made “a lot of progress” in talks with Ukrainian President Volodymyr Zelenskiy over a possible peace deal, but that it might take a few weeks to get it done and there’s no set timeline.

    Oil rose as the US-led talks failed to yield a breakthrough, and as China vowed to support growth next year. It is still on track for a fifth monthly drop in December, which would be the longest losing streak in more than two years.

    Elsewhere in markets, Bitcoin rallied more than 2% while a gauge of the dollar was steady.

    The global equities gauge has risen nearly 22% in 2025, heading for a third straight annual gain and the biggest since 2019. Trends in AI as well as the path of the Fed’s interest rates are seen by investors as two of the most crucial factors that will determine how equities perform in 2026. The Fed is scheduled to release minutes from its December policy meeting later this week.

    “Stocks can continue their party into 2026 because rate cuts are coming, global growth is robust, and the worst of the tariff threats seem to be already in the price,” said Nirgunan Tiruchelvam, an analyst at Aletheia Capital.

    Stocks

    S&P 500 futures were little changed as of 6:50 a.m. London time Nasdaq 100 futures fell 0.2% Futures on the Dow Jones Industrial Average were little changed The MSCI Asia Pacific Index rose 0.3% The MSCI Emerging Markets Index rose 0.5% Hong Kong’s Hang Seng fell 0.5% The Shanghai Composite was little changed Euro Stoxx 50 futures rose 0.3% Currencies

    The Bloomberg Dollar Spot Index was little changed The euro was little changed at $1.1764 The Japanese yen rose 0.2% to 156.26 per dollar The offshore yuan was little changed at 7.0043 per dollar The British pound was little changed at $1.3494 Cryptocurrencies

    Bitcoin rose 2.6% to $89,775.64 Ether rose 3.3% to $3,032.46 Bonds

    The yield on 10-year Treasuries was little changed at 4.13% Germany’s 10-year yield was unchanged at 2.86% Britain’s 10-year yield was little changed at 4.51% Australia’s 10-year yield advanced two basis points to 4.76% Commodities

    Spot gold fell 1.1% to $4,483.53 an ounce West Texas Intermediate crude rose 1% to $57.32 a barrel This story was produced with the assistance of Bloomberg Automation.

    –With assistance from Carmeli Argana, Rita Nazareth, Ruth Carson and Abhishek Vishnoi.

    ©2025 Bloomberg L.P.

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  • Transportation and Logistics Outlook 2026 – FTI Consulting

    1. Transportation and Logistics Outlook 2026  FTI Consulting
    2. Retail Supply Chains Brace For A Redefined 2026 As Tariffs, Technology Gaps, And Nearshoring Upend Old Models  edhat
    3. State of Global Supply Chains Come 2026: Colliers  Supply & Demand Chain Executive
    4. From Supply Chains To Robotaxis: What Is Coming In 2026 For Asian Markets  FutureIOT
    5. Preparing supply chains for 2026 in 6 simple steps  Supply Chain Management Review

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  • The Concorde spy who sold secrets to Russia

    The Concorde spy who sold secrets to Russia

    Mr Doyle was not the only person to potentially sell inside secrets on the development of Concorde.

    In 1999, it was revealed a spy codenamed “Agent Ace” had also betrayed Britain.

    The agent was an aeronautical engineer recruited in 1967, according to papers smuggled out of Russia by dissident KGB officer Vasili Mitrokhin.

    It is thought Ace handed over more than 90,000 pages of detailed technical specifications.

    The agent was one of more than a dozen spies operating within Britain and passing commercial and technological secrets to the Russians at the height of the Cold War, the papers revealed.

    The secrets that made it out of Filton helped Russia build the Tupolev-144, nicknamed Concordski, and which was strikingly similar to Concorde.

    It remains unclear whether Mr Doyle did, in fact, pass on the details he claimed to have done in the interview to the KGB or any other secrets about the Concorde programme.

    For one, questions marks remain over why Mr Doyle was never prosecuted – despite admitting spying for Russia.

    UK Parliament records seen by the BBC raised that very question on the 18 October 1971.

    The Attorney General at the time said he had been consulted about the possibility of a prosecution under the Official Secrets Act, but a prosecution would be unlikely to succeed, based on the evidence, and criminal proceedings should not be started.

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  • Gift cards surge boosts retail spending despite Black Friday competition

    Gift cards surge boosts retail spending despite Black Friday competition

    A surge in gift cards and vouchers is driving more customers into stores on Boxing Day, helping what has traditionally been one of the biggest sales for retailers compete with the increasing popularity of newer promotional events like the Black Friday and Cyber Monday juggernauts.

    Gerry Harvey, the executive chairman of electronics and whitegoods giant Harvey Norman, said gift cards and vouchers now accounted for about one-fifth of all transactions, particularly on the other side of Christmas.

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  • China signals tolerance for stronger renminbi

    China signals tolerance for stronger renminbi

    Unlock the Editor’s Digest for free

    China has fixed the renminbi at its strongest level against the dollar in 15 months, a move that analysts say signals its tolerance of a gradual appreciation as its soaring exports stoke tensions with trading partners.

    The People’s Bank of China on Monday set the renminbi at 7.03 to the dollar, the strongest fix since September 30 2024. The currency has strengthened by almost 4 per cent this year against the greenback but has weakened against the euro and other currencies.

    The relative weakness of the Chinese currency has been a bugbear for American and European leaders, who see it as unfairly advantaging their exporters and contributing to China’s enormous trade surplus.

    “It’s clear we’re seeing an acceleration in renminbi strength to the end of year,” said Mansoor Mohi-uddin, chief economist at Bank of Singapore. “They’re clearly allowing the currency to rise but in a controlled way.”

    Prior to a trade truce agreed in October, US tariffs on Chinese goods were at one stage as high as 145 per cent. “Now as the tariff situation becomes a lot clearer and less troublesome, you see the currency begin the rebound,” said Mohi-uddin.

    The renminbi spot rate, which can fluctuate 2 per cent either way around the PBoC midpoint fix, has strengthened in recent weeks.

    The Chinese central bank, in a statement released last week in the wake of a Monetary Policy Committee meeting on December 18, pledged to “maintain the basic stability of the [renminbi] exchange rate at a reasonable and balanced level”.

    Even as the central bank has allowed the currency to strengthen, “the PBoC is also becoming more resistant to gains in the [renminbi], especially as they approach 7 [per dollar], which is both a psychologically important level for the PBoC and for exporters,” said Mitul Kotecha, head of foreign exchange and emerging markets macro strategy at Barclays.

    “Never gamble on a one-way appreciation” of the renminbi, the state-owned Shanghai Securities News said in an article published on Monday.

    Analysts doubted the PBoC would allow an appreciation that would undermine its export powerhouse economy, given its 5 per cent GDP growth target.

    “The golden goose has been the exports trend, which has been the biggest contributor to growth this year,” said Kotecha.

    He added that having a strong currency at a time when other drivers of growth, such as housing, are particularly weak will make it “tough for China to achieve its growth targets”.

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  • Xu, Z. et al. NLRP inflammasomes in health and disease. Mol. Biomed. 5 (1), 14 (2024).

    Google Scholar 

  • Carroll, K., Sawden, M. & Sharma, S. DAMPs, PAMPs, NLRs, RIGs, CLRs and TLRs–Understanding the alphabet soup in the context of bone biology. Curr. Osteoporos. Rep. 23 (1), 6 (2025).

    Google Scholar 

  • Zheng, D., Liwinski, T. & Elinav, E. Inflammasome activation and regulation: toward a better Understanding of complex mechanisms. Cell. Discovery. 6 (1), 36 (2020).

    Google Scholar 

  • Fusco, R. et al. Focus on the role of NLRP3 inflammasome in diseases. Int. J. Mol. Sci. 21 (12), 4223 (2020).

    Google Scholar 

  • Van de Veerdonk, F. L. et al. Inflammasome activation and IL-1β and IL-18 processing during infection. Trends Immunol. 32 (3), 110–116 (2011).

    Google Scholar 

  • Dadkhah, M. & Sharifi, M. The NLRP3 inflammasome: mechanisms of activation, regulation, and role in diseases. Int. Rev. Immunol. 44 (2), 98–111 (2025).

    Google Scholar 

  • Jurcău, M. C. et al. The link between oxidative stress, mitochondrial dysfunction and neuroinflammation in the pathophysiology of alzheimer’s disease: therapeutic implications and future perspectives. Antioxidants 11 (11), 2167 (2022).

    Google Scholar 

  • Li, Y. et al. Targeting microglial α-synuclein/TLRs/NF-kappaB/NLRP3 inflammasome axis in parkinson’s disease. Front. Immunol. 12, 719807 (2021).

    Google Scholar 

  • Nasoohi, S., Parveen, K. & Ishrat, T. Metabolic syndrome, brain insulin resistance, and alzheimer’s disease: thioredoxin interacting protein (TXNIP) and inflammasome as core amplifiers. J. Alzheimer’s Disease. 66 (3), 857–885 (2018).

    Google Scholar 

  • Boršić, E. et al. Clustering of NLRP3 induced by membrane or protein scaffolds promotes inflammasome assembly. Nat. Commun. 16 (1), 4887 (2025).

    Google Scholar 

  • Fu, J. & Wu, H. Structural mechanisms of NLRP3 inflammasome assembly and activation. Annu. Rev. Immunol. 41 (1), 301–316 (2023).

    Google Scholar 

  • Zhang, X. et al. Inhibitors of the NLRP3 inflammasome pathway as promising therapeutic candidates for inflammatory diseases. Int. J. Mol. Med. 51 (4), 35 (2023).

    Google Scholar 

  • Kennedy, C. R. et al. A probe for NLRP3 inflammasome inhibitor MCC950 identifies carbonic anhydrase 2 as a novel target. ACS Chem. Biol. 16 (6), 982–990 (2021).

    Google Scholar 

  • Patel, V. & Shah, M. Artificial intelligence and machine learning in drug discovery and development. Intell. Med. 2 (3), 134–140 (2022).

    Google Scholar 

  • Daroch, A. & Purohit, R. MDbDMRP: A novel molecular descriptor-based computational model to identify drug-miRNA relationships. Int. J. Biol. Macromol. 287, 138580 (2025).

    Google Scholar 

  • Sharma, B. & Purohit, R. Enhanced sampling simulations to explore Himalayan phytochemicals as potential phosphodiesterase-1 inhibitor for neurological disorders. Biochem. Biophys. Res. Commun. 758, 151614 (2025).

    Google Scholar 

  • Singh, R. & Purohit, R. Determining the effect of natural compounds on mutations of Pyrazinamidase in multidrug-resistant tuberculosis: illuminating the dark tunnel. Biochem. Biophys. Res. Commun. 756, 151575 (2025).

    Google Scholar 

  • Gupta, A., Thind, A. S. & Purohit, R. EGFR AP: a predictive machine learning model for assessing small molecule activity against the epidermal growth factor receptor. RSC Med. Chem. 16 (9), 4415–4426 (2025).

    Google Scholar 

  • Hayat, C. et al. Identification of new potent NLRP3 inhibitors by multi-level in-silico approaches. BMC Chem. 18 (1), 76 (2024).

    Google Scholar 

  • Pinheiro, G. A. et al. Machine learning prediction of nine molecular properties based on the SMILES representation of the QM9 quantum-chemistry dataset. J. Phys. Chem. A. 124 (47), 9854–9866 (2020).

    Google Scholar 

  • Kaneko, H. Molecular descriptors, structure generation, and inverse QSAR/QSPR based on SELFIES. ACS Omega. 8 (24), 21781–21786 (2023).

    Google Scholar 

  • Samkhaniani, M. et al. A machine learning approach to feature selection and uncertainty analysis for biogas production in wastewater treatment plants. Waste Manage. 197, 14–24 (2025).

    Google Scholar 

  • Pantic, I. & Paunovic Pantic, J. Artificial intelligence in chromatin analysis: A random forest model enhanced by fractal and wavelet features. Fractal Fract. 8 (8), 490 (2024).

    Google Scholar 

  • Ishfaq, M. et al. Multinomial classification of NLRP3 inhibitory compounds based on large scale machine learning approaches. Mol. Diversity. 28 (4), 1849–1868 (2024).

    Google Scholar 

  • Mehrabinezhad, A., Teshnehlab, M. & Sharifi, A. A comparative study to examine principal component analysis and kernel principal component analysis-based weighting layer for convolutional neural networks. Comput. Methods Biomech. Biomedical Engineering: Imaging Visualization. 12 (1), 2379526 (2024).

    Google Scholar 

  • Abdul-Al, M. et al. A novel approach to enhancing multi-modal facial recognition: integrating convolutional neural networks, principal component analysis, and sequential neural networks. IEEE Access. 12 (2024).

  • Haji, A. Comparative analysis of autoencoder and PCA for dimensionality reduction in gene expression data. (2024).

  • Kaib, M. T. H. et al. Data size reduction approach for nonlinear process monitoring refinement using kernel PCA technique. Expert Syst. Appl. 274, 126975 (2025).

    Google Scholar 

  • Makkulau, M. et al. Variance The Estimation Eigen Value of Principal Component Analysis and Nonlinear Principal Component Analysis. in ITM Web of Conferences. EDP Sciences. (2024).

  • Frost, H. R. Eigenvectors from eigenvalues sparse principal component analysis (EESPCA). J. Comput. Graphical Statistics: Joint Publication Am. Stat. Association Inst. Math. Stat. Interface Foundation North. Am. 31 (2), 486 (2021).

    Google Scholar 

  • Eze, N. M., Asogwa, O. C. & Eze, C. M. Principal component factor analysis of some development factors in Southern Nigeria and its extension to regression analysis. J. Adv. Math. Comput. Sci. 36 (3), 132–160 (2021).

    Google Scholar 

  • Abdulhafedh, A. Incorporating k-means, hierarchical clustering and Pca in customer segmentation. J. City Dev. 3 (1), 12–30 (2021).

    Google Scholar 

  • Niazi, S. K. & Mariam, Z. Recent advances in machine-learning-based chemoinformatics: a comprehensive review. Int. J. Mol. Sci. 24 (14), 11488 (2023).

    Google Scholar 

  • Wani, M. A. & Roy, K. K. Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents. Mol. Diversity. 26 (3), 1345–1356 (2022).

    Google Scholar 

  • Shrivastava, T., Singh, V. & Agrawal, A. Autism spectrum disorder detection with kNN imputer and machine learning classifiers via questionnaire mode of screening. Health Inform. Sci. Syst. 12 (1), 18 (2024).

    Google Scholar 

  • Almatroudi, A. Integrative machine learning, virtual screening, and molecular modeling for BacA-Targeted Anti-Biofilm drug discovery against Staphylococcal infections. Crystals 14 (12), 1057 (2024).

    Google Scholar 

  • Zhang, H. et al. Machine learning methods for weather forecasting: A survey. Atmosphere 16 (1), 82 (2025).

    Google Scholar 

  • Salama, M. Optimization of regression models using machine learning: A comprehensive study with scikit-learn. Optimization of Regression Models Using Machine Learning: A Comprehensive Study with Scikit-learn| IUSRJ, 5. (2024).

  • Alemerien, K., Alsarayreh, S. & Altarawneh, E. Diagnosing cardiovascular diseases using optimized machine learning algorithms with GridSearchCV. J. Appl. Data Sci. 5 (4), 1539–1552 (2024).

    Google Scholar 

  • Padhy, S. & SMOTE-based Deep, L. S. T. M. System with GridSearchCV optimization for intelligent diabetes diagnosis. J. Electr. Syst. 20 (7s), 804–815 (2024).

    Google Scholar 

  • Mumtaz, A. et al. MPD3: a useful medicinal plants database for drug designing. Nat. Prod. Res. 31 (11), 1228–1236 (2017).

    Google Scholar 

  • Aloufi, B. H., Snoussi, M. & Sulieman, A. M. E. Antiviral efficacy of selected natural phytochemicals against SARS-CoV-2 Spike glycoprotein using structure-based drug designing. Molecules 27 (8), 2401 (2022).

    Google Scholar 

  • El-Hachem, N. et al. AutoDock and AutoDockTools for protein-ligand docking: beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) as a case study, in Neuroproteomics: Methods and Protocols. Springer.391–403. (2017).

  • Zayed, A. O. H. Optimizing protein-ligand Docking through machine learning: algorithm selection with AutoDock Vina. Discover Chem. 2 (1), 164 (2025).

    Google Scholar 

  • Kaur, J., Kaur, S. & andSingh Rational modification of the lead molecule: enhancement in the anticancer and dihydrofolate reductase inhibitory activity. Bioorg. Med. Chem. Lett. 26 (8), 1936–1940 (2016).

    Google Scholar 

  • Berendsen, H. J., van der Spoel, D. & van Drunen, R. A message-passing parallel molecular dynamics implementation. Comput. Phys. Commun. 91 (1–3), 43–56 (1995).

    Google Scholar 

  • Huang, J. & MacKerell, A. D. Jr CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data. J. Comput. Chem. 34 (25), 2135–2145 (2013).

    Google Scholar 

  • Mishra, S. et al. Classical molecular dynamics simulation identifies catechingallate as a promising antiviral polyphenol against MPOX palmitoylated surface protein. Comput. Biol. Chem. 110, 108070 (2024).

    Google Scholar 

  • Ramsey, I. S. et al. An aqueous H + permeation pathway in the voltage-gated proton channel Hv1. Nat. Struct. Mol. Biol. 17 (7), 869–875 (2010).

    Google Scholar 

  • Kognole, A. A. et al. CHARMM-GUI Drude Prepper for molecular dynamics simulation using the classical Drude polarizable force field. J. Comput. Chem. 43 (5), 359–375 (2022).

    Google Scholar 

  • Jawad, B. et al. Key interacting residues between RBD of SARS-CoV-2 and ACE2 receptor: combination of molecular dynamics simulation and density functional calculation. J. Chem. Inf. Model. 61 (9), 4425–4441 (2021).

    Google Scholar 

  • Gilson, M. K. & Zhou, H. X. Calculation of protein-ligand binding affinities. Annu. Rev. Biophys. Biomol. Struct. 36 (1), 21–42 (2007).

    Google Scholar 

  • Du, X. et al. Insights into protein–ligand interactions: mechanisms, models, and methods. Int. J. Mol. Sci. 17 (2), 144 (2016).

    Google Scholar 

  • Yasir, M. et al. Investigating the inhibitory potential of flavonoids against aldose reductase: insights from molecular docking, dynamics simulations, and gmx_MMPBSA analysis. Curr. Issues. Mol. Biol. 46 (10), 11503–11518 (2024).

    Google Scholar 

  • Kadhum, L. H. Geometry optimization of coupling allin-metformin using dft/b3lyp molecular modelling technique: geometry optimization of coupling allin-metformin using dft/b3lyp molecular modelling technique. Iraqi J. Market Res. Consumer Prot. 13 (2), 89–100 (2021).

    Google Scholar 

  • El Addali, A. et al. Theoretical study of the phosphate units stability by the Dft b3lyp/6-311 g quantum method. J. Chem. Technol. 31 (3), 477–485 (2023).

    Google Scholar 

  • Mackay, A. et al. Discovery of NP3-253, a potent brain penetrant inhibitor of the NLRP3 inflammasome. J. Med. Chem. 67 (23), 20780–20798 (2024).

    Google Scholar 

  • Bağlan, M., Gören, K. & Yıldıko, Ü. MEP analysis and molecular Docking using DFT calculations in DFPA molecule. Int. J. Chem. Technol. 7 (1), 38–47 (2023).

    Google Scholar 

  • Taher, S. R. & Hamad, W. M. Synthesis, characterization, density functional theory (DFT) analysis, and mesomorphic study of new thiazole derivatives. Bull. Chem. Soc. Ethiop. 38 (6), 1827–1842 (2024).

    Google Scholar 

  • Stuart, J. G. & Jebaraj, J. W. Synthesis, characterisation, in Silico molecular Docking and DFT studies of 2, 6-bis (4-hydroxy-3-methoxyphenyl)-3, 5-dimethylpiperidin-4-one. Indian J. Chem. (IJC). 62 (10), 1061–1080 (2023).

    Google Scholar 

  • Andonova, V. et al. Spectral characteristics, in Silico perspectives, density functional theory (DFT), and therapeutic potential of green-extracted phycocyanin from spirulina. Int. J. Mol. Sci. 25 (17), 9170 (2024).

    Google Scholar 

  • Wu, S. et al. Theoretical study on the adsorption of Sulforaphane on B 12 N 12-related nanocages based on density functional theory. New J. Chem. 47 (47), 21743–21752 (2023).

    Google Scholar 

  • Khalid, M. et al. Exploration of noncovalent interactions, chemical reactivity, and nonlinear optical properties of Piperidone derivatives: a concise theoretical approach. ACS Omega. 5 (22), 13236–13249 (2020).

    Google Scholar 

  • Solgun, D. G. et al. Synthesis of axially silicon phthalocyanine substituted with bis-(3, 4-dimethoxyphenethoxy) groups, DFT and molecular Docking studies. J. Incl. Phenom. Macrocyclic Chem. 102 (11), 851–860 (2022).

    Google Scholar 

  • Ganiev, B., Mardonov, U. & Kholikova, G. Molecular structure, HOMO-LUMO, MEP-–Analysis of triazine compounds using DFT (B3LYP) calculations. Materials Today: Proceedings, (2023).

  • Pardridge, W. M. Drug transport across the blood–brain barrier. J. Cereb. Blood flow. Metabolism. 32 (11), 1959–1972 (2012).

    Google Scholar 

  • Leeson, P. D. & Springthorpe, B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat. Rev. Drug Discovery. 6 (11), 881–890 (2007).

    Google Scholar 

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