## 1 Introduction  
Haemoglobinopathies and thalassemias are inherited genetic mutations in the \(\alpha\) and \(\beta\) subunits of haemoglobin that have been classified worldwide as endemic diseases and frequently observed in Asia, Middle East and African populations [1]. These genetic alterations lead to abnormal expression and structural changes in haemoglobin, often resulting in anemia and has been estimated that 5% of the population suffers from its symptoms [1; 2]. The diagnostic of these diseases is based on expensive and time-consuming genetic tests that are not affordable for screening large populations, making this a huge problem for national health care systems [3; 4; 5]. Type 2 diabetes is also another worldwide healthcare problem that most countries face, based on the increased number of cases over the past years suggesting effective screening programs for early detection are required [6; 7]. This early stage of the disease is called pre-diabetes and preventive medicine is considered advantageous to reduce the burden of diabetes in the healthcare systems [8]. So far, rapid, effective and affordable methodologies towards screening of haemoglobinopathies, thalassemias and pre-diabetes detection in large populations are still problematic due to economic and technical constraints [8; 9].  
Matrix assisted laser desorption ionization (MALDI) time of flight (ToF) mass spectrometry (MS) is a direct, rapid and affordable analytical method already used in clinical microbiology for the pathogenic bacteria identification [10; 11; 12]. This methodology has been successfully implemented in clinical laboratories with demonstrated effective diagnostic power and substantial reduction in the costs per test [13; 14; 15]. Several studies have shown that the accuracy of MALDI-ToF MS allows the detection of chemical modification of biomolecules in complex mixtures such as urine and blood [16; 17; 18; 19]. The application of MALDI-ToF for the detection of haemoglobinopathies in blood was recently demonstrated by [PERSON] and [PERSON] [18]. Their proposed method has the potential of identifying not only haemoglobinopathies but also \(\alpha\)-thalassemia, \(\beta\)-thalassemia, and pre-diabetes in a single sample run using a single drop of blood. This is based on the detection and quantification of globin subunits (e.g., \(\alpha\) and \(\beta\)) and their correspondent glycated fractions in the MS as biomarkers for these diseases.  
MALDI-ToF MS has evolved towards an ultra-fast high-throughput technology, which has the potential to be applied to the screening of large populations [18; 20; 21]. However, interpretation of the quality of the MS and quantification of biomarkers for the correct diagnosis of a particular disease requires highly specialized technicians. Additionally, this can insert human errors, bias, extra costs in human resources and it is time consuming, which prevents MALDI-ToF to reach its full potential as a rapid and affordable high-throughput technology. Smart and fully automated software that optimizes time costs while also increasing accuracy can provide a solution for the implementation of MALDI in clinical laboratories. Previously, we developed an automated bioinformatic workflow that successfully pre-processes raw data, performs accurate quality control decisions and analyzes large data sets from urine MS generated by MALDI-ToF [22]. We further adapted these workflows and developed a user-friendly software tool (HbAnalizer), which was designed to perform fully automated detection of abnormalities in MS of human blood in large data sets. In this work, we present a software application as a solution for the screening of haemoglobinopathies, thalassemias and pre-diabetes in clinical laboratories.