Coronavirus disease (COVID-19) is a systemic infection targeting multiple organs. Interstitial pneumonia is the landmark feature of this condition. Severe acute respiratory symptoms requiring intensive care support arises for about one out of twenty symptomatic cases. Aminochinolone, antiviral, antibiotic, corticoid, anticoagulant and immunobiological drugs are used, mostly to treat symptoms. Only remdesivir exhibiting weak antiviral activity is approved for COVID-19. Psychotropic medications may interact with medical treatments for COVID-19. The aim of this presentation is to highlight pharmacokinetic and pharmacodynamic drug-drug interactions to be expected for medical treatments of COVID-19. Remdesivir and favipiravir exhibit hepatotoxic properties which may be enhanced under combinations with tricyclic antidepressants or agomelatine. Favipiravir, hydroxychloroquine, chloroquine, azithromycin, lopinavir/ritonavir have QT interval prolongation potential and must be considered for combinations with antidepressant and antipsychotic drugs. For hydroxychloroquine, hypoglycemic activity may give rise to endocrine disturbances. Pharmacokinetic drug-drug interactions can be expected for lopinavir/ritonavir which inhibit cytochrome P-450 (CYP) 3A4 and induce CYP2C9 and CYP2C19. Combinations with psychotropic drugs that are substrates of these enzymes (victim drugs) will affect drug concentrations in blood and lead to supra- or subtherapeutic levels. Moreover, it must be assumed that the COVID-19 infection is associated with an enhanced production of cytokines which has a known impact on CYP enzyme activities. Though studies on interactions between psychotropic medications and medical treatments for COVID-19 are lacking, multiple drug interactions can be predicted and expected considering the side effect profiles and CYP inhibitory, inducing and substrate properties of combined drugs.

There is little data on infection treatment in patients with mental disorders, including on the selection of psychotropic, antibiotic, antifungal, and antiviral medications. Bacterial, viral, and fungal infections often occur in patients with mental illnesses, and there is little data on rational pharmacotherapy in this vulnerable population. Antibiotic treatment is a common event during hospitalization in adult psychiatric hospitals and poses a risk of significant potential to almost a quarter of all patients. Most infections are bacterial infections where antibiotics are used, and this topic will be covered in this lecture.

Most patients are being treated for urinary tract infections or respiratory tract infections. The most commonly prescribed antibiotics are co-amoxiclav and cotrimoxazole, followed by ciprofloxacin and nitrofurantoin. Drug-drug interactions (DDIs) between antibiotics and psychotropics often occur, where medications with QTc prolongation potential should be avoided (e.g., some antipsychotics and antidepressants, quinolones, and cotrimoxazole). Penicillins are the most appropriate group, and quinolones should be avoided. DDIs between antibiotics and psychotropic drugs have been reported to occur in 20% of patients, which means that DDIs checking is always necessary before prescribing. Psychiatric adverse events (e.g., hallucinations, restlessness, insomnia) have also been seen in patients with mental disorders.

The participants will learn about general recommendations on antibiotic prescribing in this population, focusing on antibiotics and psychotropics, supported by evidence-based data and real clinical pharmacological tools useful for daily practice.

The outcome of first-episode psychosis (FEP) varies and may be predicted by several baseline measures. In the Helsinki Early Psychosis Study, young adults with FEP (n=97) from the Helsinki area in Finland were broadly assessed as soon as possible after first psychiatric contact for psychosis. Age- and gender-matched population controls were also assessed (n=62). The participants were followed up via appointments and medical records. We present both published and unpublished results on predictors of 12-month clinical, functional, and metabolic outcomes. More severe cognitive deficits at the beginning of treatment predicted several outcomes such as occupational status and functional level – beyond baseline positive and affective symptom levels, but not when negative symptoms were accounted for. More severe baseline obsessive-compulsive symptoms were predictive of a lower rate of remission, whereas a higher level of anxiety symptoms predicted better functional outcome, when the severity of positive symptoms was adjusted for. Adverse childhood experiences measuring cumulating psychosocial stress did not predict occupational status or functional level when positive and negative symptoms and neurocognition were controlled for, whereas in controls having experienced school bullying was associated with lower functioning. Insulin resistance in early psychosis appeared as an early marker of increased vulnerability to weight gain and abdominal obesity in young adults with FEP. Further, increased waist circumference predicted worsening low-grade inflammation, increasing further the cardiovascular risk. In sum, we have found different types of prognostic markers in FEP. Identifying the individuals at risk of less favorable outcomes could affect treatment choices in FEP.

Lipid metabolism has been an area of increased interest in psychosis research, not only due to its link to metabolic comorbidities, but also due to its putative role in the pathophysiology of psychosis. Lipid disturbances are observed already in the period preceding the onset of psychosis. For example, we performed mass spectrometry based lipidomics in a cohort of individuals at clinical high risk for psychosis (the EU-GEI study) and found that the individuals who transitioned to psychosis within a 2-year follow-up period displayed decreased levels of ether phospholipids. This finding may be of direct (patho)physiological relevance, as ether phospholipids (particularly plasmalogens, a major subgroup of ether phospholipids) are highly enriched in the brain, are supplied to the brain by the liver, have many structural and functional roles, and may act as endogenous antioxidants. Accumulating evidence also suggests that lipid disturbances play a crucial role in the development of metabolic comorbidities associated with psychotic disorders. Our lipidomic studies have shown that psychotic patients who rapidly gain weight during follow-up have elevated triglycerides (TGs) with low double bond count and carbon number at baseline. These TGs are known to be associated with non-alcoholic fatty liver disease (NAFLD) and with increased risk of type 2 diabetes. In conclusion, although the mechanisms linking dysregulation of lipid metabolism with the pathophysiology of psychosis are currently poorly understood, findings by us and others suggest that metabolic abnormalities are evident in people who are vulnerable to psychosis, and to the associated metabolic comorbidities.

In theory and practice early intervention has an indisputable role in the treatment of patients with psychotic disorders, however modern psychiatrists face challenges in their clinical work to find the balance between the best practice and available treatment options in their environment. One of the biggest challenges remains the implementation of high-cost treatment approaches in healthcare systems of middle-income countries. Moreover, one very important aspect to consider when implementing early intervention is to prepare your team for resistance against the innovation. In countries where psychiatric treatment is more hospital-oriented and out-patient care is limited to short face-to-face visits with psychiatrists, the system is rigid and unwilling to step up to more expanded treatment option, such as a team approach of more than 6 members to treat one patient. In Latvia we started our early intervention programme in 2019 (LAT-EIP), 34 patients enrolled, and 27 finished the programme. When we compared results between standard treatment and LAT-EIP, psychiatrist out-patient visits were comparable to LAT-EIP, but the rate of rehospitalization and assigned disabilities at 12 months follow-up differ dramatically: in LAT-EIP 7.4% had been readmitted and 7.4% were assigned with disability vs 36.1% and 34.4% of patients in standard treatment group, respectively, p<0.05. Nevertheless, the only hospital which continues to provide early intervention is the one which first established it. This presentation will try to explain step-by-step what enhances and what holds back innovation in psychiatry in one middle-income countries.

I will attempt to address the issues surrounding the CHR concept in light of novel data and briefly discuss emerging alternatives. The root problem of the CHR early invention strategy is the exertion of reducing early nonspecific (pluripotent) psychopathology to a unidimensional model restricted only to positive psychotic symptoms, which define the binary categories of CHR and “transition” in help-seeking populations. This major conceptual handicap undermines the validity and clinical utility. The core predictor of the “transition” rate is the degree of the risk-enrichment and not the CHR status. Even with a significant pretest risk enrichment, the prognostic accuracy is mediocre. The incidence and “transition” rates of CHR in the community are very low; therefore, CHR does not represent a cost-effective clinical target—prevention paradox. CHR succeeding early pluripotent psychopathology is already late for intervention. “Transition” is not a categorical progression but a unidimensional shift in psychotic symptoms, and therefore, influenced by the fluctuation of psychotic symptoms, leading to both false positives and underestimation of nonpsychotic psychopathology. There exists no evidence for a specific effect of any intervention in preventing “transition”; therefore, CHR is not an ideal treatment target. Binary “transition” outcome does not represent a valid phenotype for research as “transition” rates are primarily driven by the sampling heterogeneity. The multidimensional psychopathology and functioning are more clinically relevant, overarching, and service-user-centered measures to define individual risk and outcome. Guided by the public health perspective, a universal early intervention framework, underscoring improved access to care, may represent a better strategy.

Over the past few decades, psychiatry and mental health sciences have reached several major goals. The importance of mental health and the huge contribution to the burden of disability produced by mental and neurological disorders has been recognized by all and most recently also by the United Nations. Treatment technology has developed and permits the effective management of most mental disorders. Progress has also been made in the recognition of human rights of people with mental illness and those who care for them. More has to be done in these areas but there are also new tasks that are before psychiatry. These include the addition of primary prevention of mental disorders to previous efforts to ensure secondary and tertiary prevention of mental health problems; the development of appropriate ways of work in order to cope with problems of comorbidity of mental and physical disorders; and a fundamental reorientation of training in psychiatry and related sciences.

Recent years have seen a great advancement in the emerging field of Neural Computation, a study of the brain using neuronal network models. As a consequence, another field of science is being developed titled ‘Computational Psychiatry’ where neuronal network models of psychopathology help understand the possible etiology for mental disorders. With Computational Psychiatry we can begin and reformulate mental disorders as brain disorders. Etiological diagnosis in psychiatry will be the next breakthrough which will allow to effectively treat mental disorders and will bring psychiatry back to the realm of medicine Computational Psychiatry together with advances in technology, will transform psychiatry beyond recognition: With the development of the connecting internet and sensor technology (e.g., face speech recognition) mental status examination can be easily extracted and delivered over distance (tele-psychiatry). With the help of AI the extracted psychiatric phenomenology can be interpreted to match most of the diagnostic process of a skilled psychiatrist. Once achieved a continual psychiatric monitoring coupled with new technology of wireless dry-electrode electrophysiological brain imaging can begin and collect big-data. Big-data analysis stand a good chance to reveal the etiological correlations between mental disorders and their brain-related origins. Thus, etiology for mental disorders can begin to unravel. Neural modulation technology will be the answer for effective therapeutic interventions (i.e., future brain pacers).

Digital phenotyping represents a new approach aimed at measuring the human behavior by using smartphones and personal device sensors, smartphone apps, keyboard interaction, and various features of subject’s voice and speech. Data collected by a digital phenotyping smartphone application are divided into two categories: a) active data (i.e., those usually collected by using a survey modality) which require an ‘active participation’ from the subject to be generated; and, b) passive data (for instance, those data collected by using Global Positioning System (GPS) traces), usually collected without any participation or action from the subject. Digital phenotyping may theoretically enhance clinicians’ ability to early identify, diagnose and manage any mental health conditions and favoured a more personalized diagnostic and therapeutic approach to several mental conditions. The innovative and insightful approach applied by the digital phenotyping appears to find an interesting and useful application in the field of psychiatry. The digital phenotyping is in line with the new paradigm of the precision psychiatry, i.e. the new approach performed to help clinicians in customizing a psychiatric treatment for each patient, by integrating information about individual phenotypes and genotypes with biographical, clinical and biological data. A precision psychiatry approach would ideally allow clinicians to tailor clinical decision-making and stratify patients to each available treatment according to each one’s likelihood of treatment response and prognosis. Our aims are at providing a comprehensive panorama on evidence-based applications of digital phenotyping in psychiatry.

Difficulties in motor development are frequent and impairing. However, the assessment of these motor learning skills is difficult and limits early stage rehabilitation. Electronic sensors and algorithms can help to measure motor difficulties more easily and objectively. We will present a systematic review detailing these methods and challenges in Autism Spectrum Disorders (ASD). Electronic tablets, give access to handwriting features that are not usually evaluated in classical assessments. We describe how such digital features (in static, dynamic, pressure, and tilt domains) allow diagnosing dysgraphia and how they evolve during children development. From a finer analysis, three different clusters of dysgraphia emerge, longitudinal studies will allow to underline different patterns of development that seemingly require tailored remediation strategies. However, those digital features are not used in the context of conventional pen and paper therapies. It is possible to engage children with typical development in handwriting exercises by asking them to teach a robot to write. We implemented a long-term case study (20 sessions, 500 minutes in total) observing a child with severe Developmental Co-ordination Disorder who did not progress anymore with a classic pen and paper approach by enriching this setup with various training activities using real-time feedback loops (on tilt, pressure, dynamic, pauses). We show how this new method tackles previous child’s behaviour avoidances, boosting his motivation, and improving his motor and writing skills. This talk demonstrates how new motor digital features allow the implementation of innovative motor remediation interventions, which rely on fostering children’s personal characteristics and adaptation skills.