During the initial 18 months, R2D2-MH teams focused on data acquisition/augmentation and cocreation processes. We established a consolidated data repository and harmonized data from over half a million participants. Key publications include advancements in understanding autism through the lens of neurodiversity, the development of predictive models for autism, and insights into brain patterns and genetic variants associated with NDDs. We discussed the transition from a diagnosis-based research approach to one centered on developmental diversity, aiming to redefine well-being and functioning across developmental trajectories in a more nuanced manner (Hens and Van Goidsenhoven, Front. Psychiatry 2023). Our research yielded two papers focused on utilizing the ICF framework to examine autism from a neurodiversity perspective (Black et al., J Autism Dev Disord 2023) and to consider positive functional outcomes for identifying resilience factors (Black et al., Neurodiversity 2023). Additionally, we conducted investigations into the development of language and motor skills, revealing that early language abilities predicted later fine motor skills, and vice versa (Leyan et al., Autism Research 2023). In a cohort study involving 1.2 million children, we successfully developed prediction models utilizing information from routine developmental assessments to accurately forecast the likelihood of autism (Amit et al., JAMA Netw Open. 2024). Furthermore, our research efforts extended to brain imaging. One study examined the shared and distinct cortical thickness patterns in autism and ADHD (Berg et al., Molecular Autism 2023), while another explored the structural connectivity in autism and its correlation with specific gene expression in the human brain (Leyhausen et al., Biol Psychiatry 2023). We also concluded a large-scale study on the phenotypic impact of genetic variations associated with autism (Rolland et al., Nature Medicine 2023), highlighting the necessity of studying these variants beyond categorical diagnosis. Ongoing studies include research on genetic variations in NDD genes such as NRXN1, the interaction between genetics and preterm birth, and the genetic/environmental factors influencing the age at diagnosis in autism. Furthermore, we are currently codeveloping digital tools such as the CareConnect platform and a positive psychology app to enhance support for individuals and families concerned by NDD.