ABSTRACT
Bioassays were conducted under controlled conditions to determine the response of Spodoptera frugiperda (J. E. Smith) larvae fed with corn materials expressing Bacillus thuringiensis (Bt) insecticidal endotoxins: (1) VT Double Pro® (VT2P) expressing Cry1A.105-Cry2Ab2 proteins and (2) VT Triple Pro® (VT3P) expressing Cry1A.105-Cry2Ab2-Cry3Bb1 proteins. The parameters assessed were: (i) mortality rate, and (ii) growth inhibition (GI) with respect to the control. To conduct this study, larvae were collected from commercial non-Bt corn fields, in four agricultural sub-regions in Colombia, between 2018 and 2020. Fifty-two populations were assessed from the field and neonate larvae from each of the populations were used for the bioassays. The study found that mortality rates in the regions for larvae fed with VT2P corn ranged from 95.1 to 100.0%, with a growth inhibition (%GI) higher than 76.0%. Similarly, mortality rate for larvae fed with VT3P corn were between 91.4 and 100.0%, with a %GI above 74.0%. The population collected in Agua Blanca (Espinal, Tolima; Colombia) in 2020, showed the lowest mortality rate of 53.2% and a %GI of 73.5%, with respect to the control. The population that exhibited the lowest %GI was collected in 2018 in Agua Blanca (Espinal, Tolima, Colombia) with a 30.2%, growth inhibition, with respect to the control. In recent years, the use of plant tissue to monitor susceptibility to fall armyworm has proven to be useful in the resistance management program for corn in Colombia determining that the FAW populations are still susceptible to Bt proteins contained in VT2P and VT3P.
ABSTRACT
INTRODUCTION: Genomic testing is a relatively new, disruptive and complex health technology with multiple clinical applications in rare diseases, cancer and infection control. Genomic testing is increasingly being implemented into clinical practice, following regulatory approval, funding and adoption in models of care, particularly in the area of rare disease diagnosis. A significant barrier to the adoption and implementation of genomic testing is funding. What remains unclear is what the cost of genomic testing is, what the underlying drivers of cost are and whether policy differences contribute to cost variance in different jurisdictions, such as the requirement to have staff with a medical license involved in testing. This costing study will be useful in future economic evaluations and health technology assessments to inform optimal levels of reimbursement and to support comprehensive and comparable assessment of healthcare resource utilisation in the delivery of genomic testing globally. METHODS: A framework is presented that focuses on uncovering the process of genomic testing for any given laboratory, evaluating its utilisation and unit costs, and modelling the cost drivers and overall expenses associated with delivering genomic testing. The goal is to aid in refining and implementing policies regarding both the regulation and funding of genomic testing. A process-focused (activity-based) methodology is outlined, which encompasses resources, assesses individual cost components through a combination of bottom-up and top-down microcosting techniques and allows disaggregation of resource type and process step. ETHICS AND DISSEMINATION: The outputs of the study will be reported at relevant regional genetics and health economics conferences, as well as submitted to a peer-reviewed journal focusing on genomics. Human research ethics committee approval is not required for this microcosting study. This study does not involve research on human subjects, and all data used in the analysis are either publicly available.
Subject(s)
Diagnostic Techniques and Procedures , Rare Diseases , Humans , Rare Diseases/diagnosis , Rare Diseases/genetics , Cost-Benefit Analysis , Genomics , Australia , Genetic TestingABSTRACT
PURPOSE: Microcosting can provide valuable economic evidence to inform the translation of genomic sequencing to clinical practice. A systematic literature review was conducted to identify studies employing microcosting methods to estimate the cost of genomic sequencing to diagnose cancer and rare diseases. METHODS: Four electronic databases, Medline, Embase, EconLit, and Cumulated Index to Nursing and Allied Health Literature were searched. Reference lists of identified studies were also searched. Studies were included if they had estimated the cost of genome sequencing or exome sequencing for cancer or rare disease diagnosis using microcosting methods. RESULTS: Seven studies met the inclusion criteria. Cost estimates for genome sequencing and exome sequencing ranged between US$2094 and $9706 and US$716 and $4817 per patient, respectively. All studies disaggregated resource use and cost inputs into labor, equipment, and consumables, with consumables being the main cost component. Considerable differences in the level of detail used to report the steps and resources used in each of the sequencing steps limited study comparisons. CONCLUSION: Defining a standard microcosting methodology is challenging because of the heterogeneous nature of genomic sequencing. Reporting of detailed and complete sequencing procedures, inclusion of sensitivity analyses and clear justifications of resource use, and measurement of unit costs can improve comparability, transferability, and generalizability of study findings.
