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6. Correction: Detailed statistical analysis plan for ALBINO: effect of Allopurinol in addition to hypothermia for hypoxic-ischemic Brain Injury on Neurocognitive Outcome — a blinded randomized placebo-controlled parallel group multicenter trial for superiority (phase III)

Author

Engel, Corinna, Rüdiger, Mario, Benders, Manon J. N. L., van Bel, Frank, Allegaert, Karel, Naulaers, Gunnar, Bassler, Dirk, Klebermaß-Schrehof, Katrin, Vento, Maximo, Vilan, Ana, Falck, Mari, Mauro, Isabella, Metsäranta, Marjo, Vanhatalo, Sampsa, Mazela, Jan, Metsvaht, Tuuli, van der Vlught, Roselinda, and Franz, Axel R.

Published
2024
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7. Detailed statistical analysis plan for ALBINO: effect of Allopurinol in addition to hypothermia for hypoxic-ischemic Brain Injury on Neurocognitive Outcome — a blinded randomized placebo-controlled parallel group multicenter trial for superiority (phase III)

Author

Engel, Corinna, Rüdiger, Mario, Benders, Manon J. N. L., van Bel, Frank, Allegaert, Karel, Naulaers, Gunnar, Bassler, Dirk, Klebermaß-Schrehof, Katrin, Vento, Maximo, Vilan, Ana, Falck, Mari, Mauro, Isabella, Metsäranta, Marjo, Vanhatalo, Sampsa, Mazela, Jan, Metsvaht, Tuuli, van der Vlught, Roselinda, and Franz, Axel R.

Published
2024
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13. WHO global research priorities for antimicrobial resistance in human health

Author

Aanensen, David, Alanio, Alexandre, Alastruey-Izquierdo, Ana, Alemayehu, Tinsae, Al-Hasan, Majdi, Allegaert, Karel, Al-Maani, Amal Saif, Al-Salman, Jameela, Alshukairi, Abeer Nizar, Amir, Afreenish, Applegate, Tanya, Araj, George F, Villalobos, Marlen Arce, Årdal, Christine, Ashiru-Oredope, Diane, Ashley, Elizabeth A, Babin, François-Xavier, Bachmann, Laura H, Bachmann, Till, Baker, Kate Susan, Balasegaram, Manica, Bamford, Colleen, Baquero, Fernando, Barcelona, Laura Isabel, Bassat, Quique, Bassetti, Matteo, Basu, Sulagna, Beardsley, Justin, Vásquez, Grey Benoit, Berkley, James A, Bhatnagar, Anuj K, Bielicki, Julia, Bines, Julie, Bongomin, Felix, Bonomo, Robert A, Bradley, John S, Bradshaw, Catriona, Brett, Ana, Brink, Adrian, Brown, Colin, Brown, Jeremy, Buising, Kirsty, Carson, Carolee, Carvalho, Anna Cristina, Castagnola, Elio, Cavaleri, Marco, Cecchini, Michele, Chabala, Chishala, Chaisson, Richard E, Chakrabarti, Arunaloke, Chandler, Clare, Chandy, Sujith John, Charani, Esmita, Chen, Lisa, Chiara, Francesca, Chowdhary, Anuradha, Chua, Arlene, Chuki, Pem, Chun, Doo Ryeon, Churchyard, Gavin, Cirillo, Daniela, Clack, Lauren, Coffin, Susan E, Cohn, Jennifer, Cole, Michelle, Conly, John, Cooper, Ben, Corso, Alejandra, Cosgrove, Sara E, Cox, Helen, Daley, Charles L, Darboe, Saffiatou, Darton, Tom, Davies, Gerry, de Egea, Viviana, Dedeić-Ljubović, Amela, Deeves, Miranda, Denkinger, Claudia, Dillon, Jo-Anne R, Dramowski, Angela, Eley, Brian, Roberta Esposito, Susanna Maria, Essack, Sabiha Y, Farida, Helmia, Farooqi, Joveria, Feasey, Nicholas, Ferreyra, Cecilia, Fifer, Helen, Finlayson, Heather, Frick, Mike, Gales, Ana Cristina, Galli, Luisa, Gandra, Sumanth, Gerber, Jeffrey S, Giske, Christian, Gordon, Bruce, Govender, Nelesh, Guessennd, Nathalie, Guindo, Ibrehima, Gurbanova, Elmira, Gwee, Amanda, Hagen, Ferry, Harbarth, Stephan, Haze, John, Heim, Jutta, Hendriksen, Rene, Heyderman, Robert Simon, Holt, Kathryn Elizabeth, Hönigl, Martin, Hook, Edward W, Hope, William, Hopkins, Heidi, Hughes, Gwenda, Ismail, Ghada, Issack, Mohammad Iqbal, Jacobs, Jan, Jasovský, Dušan, Jehan, Fyeza, Pearson, Antonieta Jimenez, Jones, Makoto, Joshi, Mohan P, Kapil, Arti, Kariuki, Samuel, Karkey, Abhilasha, Kearns, Gregory L, Keddy, Karen Helena, Khanna, Nina, Kitamura, Akiko, Kolho, Kaija-Leena, Kontoyiannis, Dimitrios P, Kotwani, Anita, Kozlov, Roman S, Kranzer, Katharina, Kularatne, Ranmini, Lahra, Monica M, Langford, Bradley J, Laniado-Laborin, Rafael, Larsson, Joakim, Lass-Flörl, Cornelia, Le Doare, Kirsty, Lee, Hyukmin, Lessa, Fernanda, Levin, Anna S, Limmathurotsakul, Direk, Lincopan, Nilton, Lo Vecchio, Andrea, Lodha, Rakesh, Loeb, Mark, Longtin, Yves, Lye, David Chien, Mahmud, Asif Mujtaba, Manaia, Célia, Manderson, Lenore, Mareković, Ivana, Marimuthu, Kalisvar, Martin, Irene, Mashe, Tapfumanei, Mei, Zeng, Meis, Jacques F, Lyra Tavares De Melo, Flávio Augusto, Mendelson, Marc, Miranda, Angelica Espinosa, Moore, David, Morel, Chantal, Moremi, Nyambura, Moro, Maria Luisa, Moussy, Francis, Mshana, Stephen, Mueller, Arno, Ndow, Francis J, Nicol, Mark, Nunn, Andrew, Obaro, Stephen, Obiero, Christina W, Okeke, Iruka N, Okomo, Uduak, Okwor, Tochi J, Oladele, Rita, Omulo, Sylvia, Ondoa, Pascale, Ortellado de Canese, Juana Medarda, Ostrosky-Zeichner, Luis, Padoveze, Maria Clara, Pai, Madhukar, Park, Benjamin, Parkhill, Julian, Parry, Christopher M, Peeling, Rosanna, Sobreira Vieira Peixe, Luísa Maria, Perovic, Olga, Pettigrew, Melinda M, Principi, Nicola, Pulcini, Céline, Puspandari, Nelly, Rawson, Timothy, Reddy, Denasha Lavanya, Reddy, Kessendri, Redner, Paulo, Rodríguez Tudela, Juan Luis, Rodríguez-Baño, Jesús, Van Katwyk, Susan Rogers, Roilides, Emmanuel, Rollier, Christine, Rollock, Leslie, Ronat, Jean-Baptiste, Ruppe, Etienne, Sadarangani, Manish, Salisbury, David, Salou, Mounerou, Samison, Luc Hervé, Sanguinetti, Maurizio, Sartelli, Massimo, Schellack, Natalie, Schouten, Jeroen, Schwaber, Mitchell J, Seni, Jeremiah, Senok, Abiola, Shafer, William M, Shakoor, Sadia, Sheppard, Donald, Shin, Jong-Hee, Sia, Sonia, Sievert, Dawn, Singh, Ishwar, Singla, Rupak, Skov, Robert Leo, Soge, Olusegun O, Sprute, Rosanne, Srinivasan, Arjun, Srinivasan, Subasree, Sundsfjord, Arnfinn, Tacconelli, Evelina, Tahseen, Sabira, Tangcharoensathien, Viroj, Tängdén, Thomas, Thursky, Karin, Thwaites, Guy, Tigulini de Souza Peral, Renata, Tong, Deborah, Tootla, Hafsah Deepa, Tsioutis, Constantinos, Turner, Katy M, Turner, Paul, Omar, Shaheed Vally, van de Sande, Wendy WJ, van den Hof, Susan, van Doorn, Rogier, Veeraraghavan, Balaji, Verweij, Paul, Wahyuningsih, Retno, Wang, Hui, Warris, Adilia, Weinstock, Hillard, Wesangula, Evelyn, Whiley, David, White, Peter J, Williams, Phoebe, Xiao, Yonghong, Moscoso, Martin Yagui, Yang, Hsu Li, Yoshida, Sachiyo, Yu, Yunsong, Żabicka, Dorota, Zignol, Matteo, Rudan, Igor, Bertagnolio, Silvia, Dobreva, Zlatina, Centner, Chad M, Olaru, Ioana Diana, Donà, Daniele, Burzo, Stefano, Huttner, Benedikt D, Chaillon, Antoine, Gebreselassie, Nebiat, Wi, Teodora, Hasso-Agopsowicz, Mateusz, Allegranzi, Benedetta, Sati, Hatim, Ivanovska, Verica, Kothari, Kavita U, Balkhy, Hanan H, Cassini, Alessandro, Hamers, Raph L, and Weezenbeek, Kitty Van

Published
2024
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14. Low agreement between various eGFR formulae in pediatric and young adult ADPKD patients

Author

Schellekens, Pieter, Verjans, Marcelien, Janssens, Peter, Dachy, Angélique, De Rechter, Stéphanie, Breysem, Luc, and Allegaert, Karel

Subjects
Young adults -- Care and treatment, Genetic disorders -- Diagnosis -- Demographic aspects, Mathematics -- Formulae, Polycystic kidney disease -- Diagnosis -- Demographic aspects, Glomerular filtration rate -- Research, Pediatric research, Health
Abstract

Background Young autosomal dominant polycystic kidney disease (ADPKD) patients are becoming the new target population for the development of new treatment options. Determination of a reliable equation for estimated glomerular filtration rate (eGFR) from early stages is needed with the promising potential interventional therapies. Methods Prospective and longitudinal study on a cohort of 68 genotyped ADPKD patients (age range 0-23 years) with long-term follow-up. Commonly used equations for eGFR were compared for their relative performance. Results The revised Schwartz formula (CKiD) showed a highly significant decline in eGFR with aging (- 3.31 mL/min/1.73 m.sup.2/year, P < 0.0001). The recently updated equation by the Schwartz group (CKiDU25) showed a smaller (- 0.90 mL/min/1.73 m.sup.2/year) but significant (P = 0.001) decline in eGFR with aging and also showed a significant sex difference (P < 0.0001), not observed by the other equations. In contrast, the full age spectrum (FAS) equations (FAS-SCr, FAS-CysC, and the combined) showed no age and sex dependency. The prevalence of hyperfiltration is highly dependent on the formula used, and the highest prevalence was observed with the CKiD Equation (35%). Conclusions The most widely used methods to calculate eGFR in ADPKD children (CKiD and CKiDU25 equations) were associated with unexpected age or sex differences. The FAS equations were age- and sex-independent in our cohort. Hence, the switch from the CKiD to CKD-EPI equation at the transition from pediatric to adult care causes implausible jumps in eGFR, which could be misinterpreted. Having reliable methods to calculate eGFR is indispensable for clinical follow-up and clinical trials. Graphical abstract, Author(s): Pieter Schellekens [sup.1] [sup.2] [sup.3] , Marcelien Verjans [sup.4] , Peter Janssens [sup.1] [sup.5] , Angélique Dachy [sup.1] [sup.6] , Stéphanie De Rechter [sup.1] [sup.4] , Luc Breysem [sup.7] [...]

Published
2023
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18. A Population Model of Time-Dependent Changes in Serum Creatinine in (Near)term Neonates with Hypoxic-Ischemic Encephalopathy During and After Therapeutic Hypothermia

Author

Krzyzanski, Wojciech, Wintermark, Pia, Annaert, Pieter, Groenendaal, Floris, Şahin, Suzan, Öncel, Mehmet Yekta, Armangil, Didem, Koc, Esin, Battin, Malcolm R., Gunn, Alistair J., Frymoyer, Adam, Chock, Valerie Y.-L., Keles, Elif, Mekahli, Djalila, van den Anker, John, Smits, Anne, and Allegaert, Karel

Published
2024
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19. Doxapram versus placebo in preterm newborns: a study protocol for an international double blinded multicentre randomized controlled trial (DOXA-trial)

Author

Poppe, Jarinda A., Flint, Robert B., Smits, Anne, Willemsen, Sten P., Storm, Kelly K., Nuytemans, Debbie H., Onland, Wes, Poley, Marten J., de Boode, Willem P., Carkeek, Katherine, Cassart, Vincent, Cornette, Luc, Dijk, Peter H., Hemels, Marieke A. C., Hermans, Isabelle, Hütten, Matthias C., Kelen, Dorottya, de Kort, Ellen H. M., Kroon, André A., Lefevere, Julie, Plaskie, Katleen, Stewart, Breanne, Voeten, Michiel, van Weissenbruch, Mirjam M., Williams, Olivia, Zonnenberg, Inge A., Lacaze-Masmonteil, Thierry, Pas, Arjan B.te, Reiss, Irwin K. M., van Kaam, Anton H., Allegaert, Karel, Hutten, G. Jeroen, and Simons, Sinno H. P.

Published
2023
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21. Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates

Author

Tang, Bo-Hao, Zhang, Jin-Yuan, Allegaert, Karel, Hao, Guo-Xiang, Yao, Bu-Fan, Leroux, Stephanie, Thomson, Alison H., Yu, Ze, Gao, Fei, Zheng, Yi, Zhou, Yue, Capparelli, Edmund V., Biran, Valerie, Simon, Nicolas, Meibohm, Bernd, Lo, Yoke-Lin, Marques, Remedios, Peris, Jose-Esteban, Lutsar, Irja, Saito, Jumpei, Jacqz-Aigrain, Evelyne, van den Anker, John, Wu, Yue-E., and Zhao, Wei

Published
2023
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25. Management of preterm labor: Clinical practice guideline and recommendation by the WAPM-World Association of Perinatal Medicine and the PMF-Perinatal Medicine Foundation

Author

Dagklis, Themistoklis, Akolekar, Ranjit, Villalain, Cecilia, Tsakiridis, Ioannis, Kesrouani, Assaad, Tekay, Aydin, Plasencia, Walter, Wellmann, Sven, Kusuda, Satoshi, Jekova, Nelly, Prefumo, Federico, Volpe, Nicola, Chaveeva, Petya, Allegaert, Karel, Khalil, Asma, and Sen, Cihat

Published
2023
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27. Global research priorities on COVID-19 for maternal, newborn, child and adolescent health

Author

ASM, Nawshad Uddin Ahmed, Maamri, Abdellatif, Falade, Adegoke G, Ayede, Adejumoke Idowu, Bhutta, Adnan, Gambhir, Ajay, Tagarro, Alfredo, Abdelmegeid, Ali, Ahmadi, Ali Reza, Barros, Aluísio JD, Mekasha, Amha, Srinivasaiyer, Anantha Kumar, da Silva, André Ricardo Araujo, Schultz, Andreas, Fatima, Batool, Dhar, Bishnupada, Magowan, Brian, Wills, Bridget, Raynes-Greenow, Camille, Homer, Caroline, Maclennan, Carolyn, Ward, Catherine, Garcia, Daniel Martinez, Ross, David, Murdoch, David, Wilson, Deborah Joy, Adejuyigbe, Ebun, Stasii, Ecaterina, Scudder, Elaine, Sacks, Emma, McCollum, Eric D, Althabe, Fernando, Russell, Fiona, Kumar, GS, Sommerfelt, Halvor, Graham, Hamish, Blencowe, Hannah, Tappis, Hannah, Saloojee, Haroon, Masaud, Hesham Abdussalam Ben, Tiwary, Hiresh, Asiodu, Ifeyinwa, Newton, James B, Bourdaire, Jessica, Adze, Joel Amwe, Martines, Jose, Lozano, Juan M, Walson, Judd, Rankin, Judith, Allegaert, Karel, Pellé, Karell G, Edmond, Karen, Rabiei, Katayoun, Rasmussen, Kathleen M, Yunis, Khalid, Ferguson, Laura, Greenslade, Leith, Kiapi, Lilian, Noguchi, Lisa, Bont, Louis, Day, Louise T, Mofenson, Lynne, Aboumayaleh, Maher, Aquzouz, Majda, Wahba, Mamdouh, Nagai, Mari, Knight, Marian, Melkumova, Marina, Jenyfa, Mariyam, Neuman, Mark I, Meremikwu, Martin, Kinney, Mary, Gravett, Michael, Hawkes, Michael T, Pacqué, Michel, Walsh, Michele, McGuire, Michelle K, AlShawafi, Nagiba AAbdulghani, Khuri-Bulos, Najwa, Thacker, Naveen, Rollins, Nigel, Kissoon, Niranjan, Starets, Olena, Picone, Olivier, Oladapo, Olufemi T, Erdeve, Omer, Smith, P Brian, Van de Perre, Philippe, Kumar, Praveen, Mangtani, Punam, Abbas, Qalab, Khatoon, Rabeya, Bahl, Rajiv, Lodha, Rakesh, Grais, Rebecca, Richards-Kortum, Rebecca, Rasaily, Reeta, Aryeetey, Richmond, Pattinson, Robert, and Petrucci, Roberta

Subjects
Public Health, Health Sciences, Pediatric, Prevention, Perinatal Period - Conditions Originating in Perinatal Period, Good Health and Well Being, Adolescent, Adolescent Health, COVID-19, Child, Child Health, Female, Global Health, Humans, Infant, Newborn, Pandemics, Research, SARS-CoV-2, COVID-19 Research Prioritization Group on MNCAH, Public Health and Health Services, Public health
Abstract

BackgroundThis research prioritization aimed to identify major research gaps in maternal, newborn, child and adolescent health (MNCAH) to help mitigate the direct and indirect effects of the COVID-19 pandemic.MethodsWe adapted the Child Health and Nutrition Research Initiative methodology. We defined scope, domains, themes and scoring criteria. We approached diverse global experts via email to submit their research ideas in MNCAH and MNCAH-related cross-cutting/health systems area. We curated the research ideas as research questions (RQs) and sent them to the consenting experts for scoring via the online link. For each RQ, the research priority score (RPS) was calculated as an average of individual criterion scores and ranked based on RPS in each area.ResultsWe identified top-ranked 10 RQs in each maternal, newborn, and child and adolescent health and 5 in the cross-cutting/health systems area. In maternal health, indirect effects on care, measures to improve care, health risks and outcomes, and preventing and managing SARS-CoV-2 infection/COVID-19 disease were priority RQs. In newborn health, clinical characterization and managing SARS-CoV-2 infection/COVID-19 disease, mode of transmission and interventions to prevent transmission were the focus. For child and adolescent health, top-ranked RQs were indirect effects on care, clinical status and outcomes, interventions to protect against SARS-CoV-2 infection/COVID-19 disease, and educational institute-related RQs. The cross-cutting RQs were the effects of the pandemic on availability, access, care-seeking and utilization of MNCAH services and potential solutions.ConclusionsWe call on partners, including governments, non-governmental organizations, research institutes, and donors, to address this urgent research agenda.

Published
2021

34. Is noxious stimulus-evoked electroencephalography response a reliable, valid, and interpretable outcome measure to assess analgesic efficacy in neonates? A systematic review and individual participant data (IPD) meta-analysis protocol

Author

Baxter, Luke, primary, Vaart, Marianne van der, additional, Cobo, Maria M, additional, Gunawan, Patricia, additional, Allegaert, Karel, additional, Davis, Jonathan M, additional, Turner, Mark, additional, Ward, Robert, additional, Darsey, Edress, additional, Sheppard, James P, additional, Bhatt, Aomesh, additional, Anker, John van den, additional, Massaro, An N, additional, Walls, Ramona L, additional, Song, Laura S, additional, Singh, Kanwaljit, additional, N/A, INC Pain working party authorship group, additional, and Slater, Rebeccah, additional

Published
2024
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41. Effects of hypothermia and hypoxia on cytochrome P450‐mediated drug metabolism in neonatal Göttingen minipigs.

Author

Stroe, Marina‐Stefania, De Clerck, Laura, Dhaenens, Maarten, Dennis, Rachel Siân, Deforce, Dieter, Carpentier, Sebastien, Annaert, Pieter, Leys, Karen, Smits, Anne, Allegaert, Karel, Van Ginneken, Chris, and Van Cruchten, Steven

Subjects
ASPHYXIA neonatorum, GENE expression, THERAPEUTIC hypothermia, LIVER microsomes, CYTOCHROME P-450
Abstract

Asphyxiated neonates often undergo therapeutic hypothermia (TH) to reduce morbidity and mortality. As perinatal asphyxia and TH impact neonatal physiology, this could also influence enzyme functionality. Therefore, this study aimed to unravel the impact of age, hypothermia and hypoxia on porcine hepatic cytochrome P450 (CYP) gene expression, protein abundance and activity. Hepatic CYP expression, protein abundance and activity were assessed in naive adult and neonatal Göttingen minipigs, alongside those from an (non‐survival) in vivo study, where four conditions—control (C), therapeutic hypothermia (TH), hypoxia (H), hypoxia and TH (H + TH)—were examined. Naive neonatal Göttingen minipigs exhibited 75% lower general CYP activity and different gene expression patterns than adults. In vitro hypothermia (33°C) decreased general CYP activity in adult liver microsomes by 36%. Gene expression was not different between TH and C while hypoxia up‐regulated several genes (i.e., CYP3A29 [expression ratio; ER = 5.1472] and CYP2C33 [ER = 3.2292] in the H group and CYP2C33 [ER = 2.4914] and CYP2C42 [ER = 4.0197] in the H + TH group). The medical treatment and the interventions over 24 h, along with hypoxia and TH, affected the protein abundance. These data on CYP expression, abundance and activity in young animals can be valuable in building physiologically‐based pharmacokinetic models for neonatal drug dose predictions. [ABSTRACT FROM AUTHOR]

Published
2024
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42. A population pharmacokinetic model for sertraline in women during the perinatal period—A contribution from the ConcePTION project.

Author

Monfort, Anaëlle, Cardoso, Evelina, Eap, Chin B., Ansermot, Nicolas, Crettol, Severine, Fischer Fumeaux, Céline J., Graz, Myriam Bickle, Harari, Mathilde Morisod, Weisskopf, Etienne, Gandia, Peggy, Allegaert, Karel, Annaert, Pieter, Nordeng, Hedvig, Hascoët, Jean‐Michel, Claris, Olivier, Epiney, Manuella, Ferreira, Ema, Leclair, Grégoire, Csajka, Chantal, and Panchaud, Alice

Subjects
FAT content of milk, CORD blood, BREAST milk, PERINATAL period, PREGNANT women, BREASTFEEDING
Abstract

Aims: Sertraline is frequently prescribed for mental health conditions in both pregnant and breastfeeding women. According to the limited available data, only small amounts of sertraline are transferred into human milk, yet with a large amount of unexplained interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model to describe the pharmacokinetics of sertraline during the perinatal period and explain interindividual variability. Methods: Pregnant women treated with sertraline were enrolled in the multicenter prospective cohort SSRI‐Breast Milk study. A popPK model for sertraline maternal plasma and breast milk concentrations was developed and allowed estimating the milk‐to‐plasma ratio (MPR). An additional fetal compartment allowed cord blood concentrations to be described. Several covariates were tested for significance. Ultimately, model‐based simulations allowed infant drug exposure through placenta and breast milk under various conditions to be predicted. Results: Thirty‐eight women treated with sertraline were included in the study and provided 89 maternal plasma, 29 cord blood and 107 breast milk samples. Sertraline clearance was reduced by 42% in CYP2C19 poor metabolizers compared to other phenotypes. Doubling milk fat content increased the MPR by 95%. Simulations suggested a median daily infant dosage of 6.9 μg kg−1 after a 50 mg maternal daily dose, representing 0.95% of the weight‐adjusted maternal dose. Median cord blood concentrations could range from 3.29 to 33.23 ng mL−1 after maternal daily doses between 25 and 150 mg. Conclusions: Infant exposure to sertraline, influenced by CYP2C19 phenotype and breast milk fat content, remains low, providing reassurance regarding the use of sertraline during pregnancy and breastfeeding. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Physiologically Based Pharmacokinetic Modeling to Assess the Impact of Pathophysiological Changes in Neonates: Strengths, Weaknesses, and Next Steps.

Author

Allegaert, Karel

Subjects
*CHILD patients, *PREMATURE infants, *CLINICAL pharmacology, *DRUG monitoring, *BIOLOGICAL products, *ASPHYXIA neonatorum, *BLOOD flow, *LACTATION, *KNOWLEDGE gap theory
Abstract

The article explores the use of physiologically based pharmacokinetic modeling to evaluate the impact of pathophysiological changes in neonates, addressing challenges in drug development for this population. It underscores the significance of comprehending pharmacokinetics and pharmacodynamics for safe and effective pharmacotherapy. The strengths and weaknesses of extrapolation tools like population pharmacokinetic modeling and physiologically based pharmacokinetic modeling are discussed, with a call for collaborative efforts among clinical researchers, data scientists, and modelers to refine these models for neonatal drug development. Recent research has shown progress in pharmacokinetics modeling for neonates, focusing on improving drug development and dose precision, particularly in therapeutic hypothermia, and predicting medicine concentrations in human milk using PBPK modeling for projects like ConcePTION. [Extracted from the article]

Published
2024
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44. Evaluation of the effect of CYP2D6 and OCT1 polymorphisms on the pharmacokinetics of tramadol: Implications for clinical safety and dose rationale in paediatric chronic pain.

Author

Healy, Paul, Allegaert, Karel, and Della Pasqua, Oscar

Subjects
*CHILD patients, *CHRONIC pain, *TRAMADOL, *CYTOCHROME P-450 CYP2D6, *GENETIC polymorphisms
Abstract

Aims Methods Results Conclusions Our investigation aimed to assess the dose rationale of tramadol in paediatric patients considering the effect of CYP2D6/OCT1 polymorphisms on systemic exposure. Recommendations were made for the oral dose of tramadol to be used in a prospective study in children (3 months to < 18 years old) with chronic pain.Intravenous pharmacokinetic and genotype data from neonatal patients (n = 46) were available for this analysis. The time course of tramadol and O‐desmethyltramadol (M1) concentrations was characterized using a nonlinear mixed effects approach in conjunction with extrapolation principles. Clinical trial simulations were then implemented to explore the effects of polymorphism, maturation and developmental growth on the disposition of tramadol and M1. Reported efficacious exposure range in adult subjects were used as reference.The pharmacokinetics of tramadol and M1 was characterized by a two‐compartment model. The total clearance of tramadol (CLPP) comprised CYP2D6‐mediated metabolism (CLPM) and other pathways (CLPO). Age‐related changes in CLPM, CLPO and M1 clearance (CLMO) were described by a sigmoid function, with CYP2D6 as a covariate on CLPP and CLPM,  and OCT1 on CLMO. Simulation scenarios including different CYP2D6/OCT1 combinations revealed that steady‐state concentrations are above the putative ranges for analgesia in >15% and >70% of subjects after doses of 3 and 8 mg/kg, respectively.In the absence of genotyping, reference exposure ranges can be used to define the dose rationale for tramadol in paediatric chronic pain. However, a starting dose of 0.5 mg/kg/day should be considered, followed by stepwise titration to the desired analgesic response. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Applying Neural ODEs to Derive a Mechanism‐Based Model for Characterizing Maturation‐Related Serum Creatinine Dynamics in Preterm Newborns.

Author

Bräm, Dominic Stefan, Koch, Gilbert, Allegaert, Karel, van den Anker, John, and Pfister, Marc

Subjects
BIOLOGICAL models, COMPUTER simulation, PREDICTION models, PUBERTY, CREATININE, ARTIFICIAL neural networks, GESTATIONAL age, MACHINE learning, BIRTH weight
Abstract

Serum creatinine in neonates follows complex dynamics due to maturation processes, most pronounced in the first few weeks of life. The development of a mechanism‐based model describing complex dynamics requires high expertise in pharmacometric (PMX) modeling and substantial model development time. A recently published machine learning (ML) approach of low‐dimensional neural ordinary differential equations (NODEs) is capable of modeling such data from newborns automatically. However, this efficient data‐driven approach in itself does not result in a clinically interpretable model. In this work, an approach to deriving an interpretable model with reasonable PMX‐type functions is presented. This "translation" was applied to derive a PMX model for serum creatinine in neonates considering maturation processes and covariates. The developed model was compared to a previously published mechanism‐based PMX model whereas both models had similar mechanistic structures. The developed model was then utilized to simulate serum creatinine concentrations in the first few weeks of life considering different covariate values for gestational age and birth weight. The reference serum creatinine values derived from these simulations are consistent with observed serum creatinine values and previously published reference values. Thus, the presented NODE‐based ML approach to model complex serum creatinine dynamics in newborns and derive interpretable, mathematical‐statistical components similar to those in a conventional PMX model demonstrates a novel, viable approach to facilitate the modeling of complex dynamics in clinical settings and pediatric drug development. [ABSTRACT FROM AUTHOR]

Published
2024
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46. Drug related adverse event assessment in neonates in clinical trials and clinical care.

Author

Yalcin, Nadir, van den Anker, John, Samiee-Zafarghandy, Samira, and Allegaert, Karel

Subjects
DRUG side effects, HEALTH care teams, CLINICAL pharmacology, CLINICAL trials, CLINICAL medicine, DRUG labeling
Abstract

Introduction: Assessment of drug-related adverse events is essential to fully understand the benefit–risk balance of any drug exposure, weighing efficacy versus safety. This is needed for both drug labeling and clinical decision-making. Assessment is based on seriousness, severity and causality, be it more difficult to apply in neonates. Adverse event detection or prevention in the neonatal clinical setting is also more complicated because of polypharmacy, and off-label or unlicensed pharmacotherapy. Areas covered: Tools became available to assess severity and causality of adverse events in neonates recruited in clinical trials. The first version of the Neonatal Adverse Event severity score (NAESS) reduced the inter-observer variability. Causality tools like the Naranjo score were also tailored to neonates. These tools are also instrumental to support proactive pharmacovigilance in clinical care, while multidisciplinary care teams and computerized pharmacovigilance using advanced data analysis, like machine learning are emerging approaches to develop effective decision strategies. Expert opinion: All stakeholders involved in development of medicines or its clinical use should be aware of the limitations of the currently available assessment tools. Extension and optimization of these tools, advanced data analysis approaches, and capturing the variability in time-dependent physiology are warranted to improve pharmacovigilance in neonates. [ABSTRACT FROM AUTHOR]

Published
2024
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48. Pharmacokinetic/Pharmacodynamic Modelling of Allopurinol, its Active Metabolite Oxypurinol, and Biomarkers Hypoxanthine, Xanthine and Uric Acid in Hypoxic-Ischemic Encephalopathy Neonates

Author

Chu, Wan-Yu, Annink, Kim V., Nijstad, A. Laura, Maiwald, Christian A., Schroth, Michael, Bakkali, Loubna el, van Bel, Frank, Benders, Manon J. N. L., van Weissenbruch, Mirjam M., Hagen, Anja, Franz, Axel R., Dorlo, Thomas P. C., Allegaert, Karel, and Huitema, Alwin D. R.

Published
2022
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